Roman Bartak - Profile on Academia.edu (original) (raw)

Papers by Roman Bartak

Research paper thumbnail of Some Thoughts on Robustness in Multi-Agent Path Finding

Proceedings of the AAAI Symposium Series, Jan 21, 2024

Multi-agent path finding deals with finding collision free paths for a group of agents moving to ... more Multi-agent path finding deals with finding collision free paths for a group of agents moving to given destinations. The off-line generated plan is assumed to be blindly executed on robots, which brings issues when something is not going according to the plan. This short paper discusses robustness as a way to prevent the issues with uncertainty, dynamicity, and possible involvement of other (uncontrolled) agents.

Research paper thumbnail of On modeling planning problems in tabled logic programming

Current research in planning focuses mainly on so called domain independent models using the Plan... more Current research in planning focuses mainly on so called domain independent models using the Planning Domain Description Language (PDDL) as the domain modeling language. This declarative modeling approach embraces the idea of a physics-only model describing how actions change the world. However, PDDL omits information about why and when the actions should be applied to reach the goal, which significantly decreases the practical applicability of PDDL. There exist approaches such as Hierarchical Task Networks (HTN) and control rules that add this type of information to the model with the pay-off of increased efficiency but also with the downside of increased complexity and code sizes. In this paper we propose a modeling framework for planning problems based on tabled logic programming that exploits a planner module in the Picat language. This modeling framework supports structured description of world states as well as inclusion of control knowledge and heuristics in the action model. By using problems from the International Planning Competition, we experimentally demonstrate that this modeling framework achieves results comparable to planners with control rules and HTN while keeping the size of the domain model much smaller. We also show that it gives much better solving efficiency than the state-of-the-art domain-independent PDDL planners.

Research paper thumbnail of Replanning in Predictive-reactive Scheduling

Achieving optimal results in real-life production scheduling is precluded by a number of problems... more Achieving optimal results in real-life production scheduling is precluded by a number of problems. One such problem is dynamics of environments with unavailable resources (such as machine breakdowns and ill workers) and new demands (e.g. new orders) coming during the schedule execution. Traditional approach to react to unexpected events occurring on the shop floor is generating a new schedule from scratch. Complete rescheduling, however, may require excessive computation time. Moreover, the recovered schedule may deviate a lot from the ongoing schedule. Some work has focused on tackling these shortcomings, but none of the existing approaches tries to substitute jobs that cannot be executed with a set of alternative jobs. This paper reviews techniques related to predictive-reactive scheduling and suggests the future goal, which is to propose algorithms for dealing with unexpected events using the possibility of alternative processes.

Research paper thumbnail of Searching for Sequential Plans Using Tabled Logic Programming

Logic programming provides a declarative framework for modeling and solving many combinatorial pr... more Logic programming provides a declarative framework for modeling and solving many combinatorial problems. Until recently, it was not competitive with state of the art planning techniques partly due to search capabilities limited to backtracking. Recent development brought more advanced search techniques to logic programming such as tabling that simplifies implementation and exploitation of more sophisticated search algorithms. Together with rich modeling capabilities this progress brings tabled logic programing on a par with current best planners. The paper brings an initial experimental study comparing various approaches to search for sequential plans in the Picat planning module.

Research paper thumbnail of On Total-Order HTN Plan Verification with Method Preconditions – An Extension of the CYK Parsing Algorithm

Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we consider the plan verification problem for totally ordered (TO) HTN planning. T... more In this paper, we consider the plan verification problem for totally ordered (TO) HTN planning. The problem is proved to be solvable in polynomial time by recognizing its connection to the membership decision problem for context-free grammars. Currently, most HTN plan verification approaches do not have special treatments for the TO configuration, and the only one features such an optimization still relies on an exhaustive search. Hence, we will develop a new TOHTN plan verification approach in this paper by extending the standard CYK parsing algorithm which acts as the best decision procedure in general.

Research paper thumbnail of Parsing-Based Recognition of Hierarchical Plans Using the Grammar Constraint

The International FLAIRS Conference Proceedings

Plan recognition is the problem of recognizing a goal task and an agent’s plan based on the obser... more Plan recognition is the problem of recognizing a goal task and an agent’s plan based on the observed actions. Plan recognition techniques can be employed in multiagent systems, behaviour recognition, computer security, and other fields related to artificial intelligence. Hierarchical task networks (HTN) describe the decomposition hierarchy of tasks in planning problems. In HTN plan recognition, a prefix of the plan (actions observed so far) is given as an input, and the aim is to find a task that decomposes into a sequence of actions with the given prefix. In this paper, we show how the performance of parsing-based HTN plan recognition can be improved by restricting possible suffixes of the given prefix based on generalized arc consistency of a corresponding context-free grammar.

Research paper thumbnail of Multi-Agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way?

Proceedings of the 15th International Conference on Agents and Artificial Intelligence

This paper extends a study on improving the performance of reduction-based solvers for the proble... more This paper extends a study on improving the performance of reduction-based solvers for the problem of multi-agent pathfinding. The task is to navigate a set of agents in a graph without collisions. Solvers that reduce this problem to other formalisms often have issues scaling to larger instances in terms of the graph size. A previous study suggests that pruning the graph of most vertices based on a randomly chosen shortest path for each agent. In this paper, we study the effect of different choices of these paths.

Research paper thumbnail of On Heuristics for Parsing-based Verification of Hierarchical Plans with a Goal Task

Proceedings of the ... International Florida Artificial Intelligence Research Society Conference, May 4, 2022

Verification of hierarchical plans deals with the problem if a given action sequence is a valid h... more Verification of hierarchical plans deals with the problem if a given action sequence is a valid hierarchical plan -the action sequence can be obtained by decomposing a particular (goal) task using given decomposition methods. The existing parsing-based verification approach greedily composes actions until it obtains the goal task. Greediness implies that this approach also generates tasks unrelated to the goal task. In this paper, we study the use of heuristics when creating new tasks. We also ask whether the prior knowledge of the goal task improves efficiency.

Research paper thumbnail of Guiding Planning Engines by Transition-Based Domain Control Knowledge

Domain-independent planning requires only to specify planning problems in a standard language (e.... more Domain-independent planning requires only to specify planning problems in a standard language (e.g. PDDL) in order to utilise planning in some application. Despite a huge advancement in domain-independent planning, some relatively-easy problems are still challenging for existing planning engines. Such an issue can be mitigated by specifying Domain Control Knowledge (DCK) that can provide better guidance for planning engines. In this paper, we introduce transition-based DCK, inspired by Finite State Automata, that is efficient as demonstrated empirically, planner-independent (can be encoded within planning problems) and easy to specify.

Research paper thumbnail of An Ad-hoc Planner for the Mars Express Mission

Complete planning and scheduling of all spacecraft operations is a challenging area with the remo... more Complete planning and scheduling of all spacecraft operations is a challenging area with the remote agent experiment at Deep Space 1 being a pioneering system. Still the complete approach is rare in practice. For example, in the Mars Express (MEX) mission, planning and scheduling techniques are used to solve some subproblems namely scheduling command upload and data download. In this paper we describe an approach to generate a complete schedule of the spacecraft that includes planning and scheduling of science, command uplink, data downlink, maintenance, and pointing operations. The proposed solving approach was designed to plan operations on the Mars Express (MEX) mission and it was motivated by the MEX challenge at the Fourth International Competition on Knowledge Engineering for Planning and Scheduling. The method is based on incremental addition of operations to a partial schedule and modifying the time allocation of already scheduled operations to fit the newly added operation....

Research paper thumbnail of Foundations of constraint programming

Constraint programming represents Constraint programming represents one of the closest approaches... more Constraint programming represents Constraint programming represents one of the closest approaches one of the closest approaches computer science has yet made to the computer science has yet made to the Holy Grail of programming: the user Holy Grail of programming: the user states the problem, the computer states the problem, the computer solves it." solves it.

Research paper thumbnail of Minimization of useless work in resource failure recovery of workflow schedules

2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2017

Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments... more Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments with unforeseen events occurring during the execution of a schedule. Namely, in the case of a resource failure, it may be necessary to process a lot of work again, or a feasible schedule recovery may not exist at all. Moreover, the time window within which the ongoing schedule must be updated may be very short, and too timeconsuming computation of the schedule may lead to a failure of the scheduling mechanism and setback in production. Our approach in the area of predictive-reactive scheduling is to allow for substitution of tasks, which cannot be executed, with a set of alternative tasks. This paper makes use of the model of the hierarchical workflows and gives an SMT and a CSP models to recover an ongoing schedule from a resource failure with the objective to minimize the work processed in vain. The experimental analysis identified parameters for which the SMT model clearly outperform...

Research paper thumbnail of Colored Multi-Agent Path Finding: Solving Approaches

The International FLAIRS Conference Proceedings, 2021

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set ... more Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents moving in a shared environment while each agent has specified its destination. Colored MAPF generalizes MAPF by defining groups of agents that share a set of destination locations. In the paper, we evaluate several approaches to optimally solve the colored MAPF problem, namely, a method based on network flows, an extended version of conflict-based search, and two models using Boolean satisfiability. We also investigate methods for obtaining lower bounds on optimal solutions based on constraint and continuous relaxation techniques.

Research paper thumbnail of Multi-Agent Path Finding on Ozobots

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, Aug 1, 2019

Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (... more Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (mobile robots) moving on a graph. There exists several abstract models describing the problem with various types of constraints. The demo presents software to evaluate the abstract models when the plans are executed on Ozobots, small mobile robots developed for teaching programming. The software allows users to design the grid-like maps, to specify initial and goal locations of robots, to generate plans using various abstract models implemented in the Picat programming language, to simulate and to visualise execution of these plans, and to translate the plans to command sequences for Ozobots.

Research paper thumbnail of Iterative Forward Search Algorithm: Combining Local Search with Maintaining Arc Consistency and a Conflict-Based Statistics

Lecture Notes in Computer Science, 2004

The paper presents an iterative forward search framework for solving constraint satisfaction and ... more The paper presents an iterative forward search framework for solving constraint satisfaction and optimization problems. This framework combines ideas of local search, namely improving a solution by local steps, with principles of depth-first search, in particular extending a partial feasible assignment towards a solution. Within this framework, we also propose and study a conflict-based statistics and explanationbased arc consistency maintenance. To show the versatility of the proposed framework, the dynamic backtracking algorithm with maintaining arc consistency is presented as a special instance of the iterative forward search framework. The presented techniques are compared on random constraint satisfaction problems and a real-life lecture timetabling problem.

Research paper thumbnail of Constraint Hierarchy Networks

Research paper thumbnail of Revisiting Constraint Models for Planning Problems

Lecture Notes in Computer Science, 2009

Planning problems deal with finding a (shortest) sequence of actions that transfer the initial st... more Planning problems deal with finding a (shortest) sequence of actions that transfer the initial state of the world into a desired state. Frequently such problems are solved by dedicated algorithms but there exist planners based on translating the planning problem into a different formalism such as constraint satisfaction or Boolean satisfiability and using a general solver for this formalism. The paper describes how to enhance existing constraint models of planning problems by using techniques such as symmetry breaking (dominance rules), singleton consistency, and lifting.

Research paper thumbnail of On Generators of Random Quasigroup Problems

Lecture Notes in Computer Science, 2006

Problems that can be sampled randomly are a good source of test suites for comparing quality of c... more Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of structured random problems that are closer to real-life problems and hence more suitable for benchmarking. In this paper, we describe in detail generators for Quasigroup Completion Problem (QCP) and Quasigroups with Holes (QWH). In particular, we study an improvement of the generator for QCP that produces a larger number of satisfiable problems by using propagation through the all-different constraint. We also re-formulate the algorithm for generating QWH that is much faster than the original generator. Finally, we provide an experimental comparison of all presented generators.

Research paper thumbnail of Constructive Negation in CLP(H)

Inclusion of negation into logic programs is considered traditionally to be painful as the incorp... more Inclusion of negation into logic programs is considered traditionally to be painful as the incorporation of full logic negation tends to super-exponen tial time complexity of the prover. Therefore the alternative approaches to negation in logic programs are studied and among them, the procedural negation as failure sounds to be the most successful and the most widely used. However, with the spread of Constraint Logic Programming (CLP), a different approach called constructive negation becomes more popular. The reasons for acceptance of constructive negation are the preservation of the advantages of the negation as failure, i.e., efficiency and handling special features of the language, and, at the same time, while removing the main drawbacks, i.e., handling ground negative subgoals and usage as a test only. In this paper we present a constructive approach to negation in logic programs. We concentrate on implementation aspects of constructive negation here, i.e., on the design of CLP...

Research paper thumbnail of Constructive Negation and Constraints

Inclusion of negation into logic programs is considered traditionally to be painful as the incorp... more Inclusion of negation into logic programs is considered traditionally to be painful as the incorporation of full logic negation tends to super-exponen tial time complexity of the prover. Therefore the alternative approaches to negation in logic programs are studied and among them, the procedural negation as failure sounds to be the most successful and the most widely used. However, Constraint Logic Programming (CLP) is offering a different approach called constructive negation, that is becoming more popular. In this paper we present a constructive approach to negation in logic programs. We concentrate on implementatio n aspects of constructive negation here, i.e., on the design of CLP( H) system, where H is the Herbrand Universe.

Research paper thumbnail of Some Thoughts on Robustness in Multi-Agent Path Finding

Proceedings of the AAAI Symposium Series, Jan 21, 2024

Multi-agent path finding deals with finding collision free paths for a group of agents moving to ... more Multi-agent path finding deals with finding collision free paths for a group of agents moving to given destinations. The off-line generated plan is assumed to be blindly executed on robots, which brings issues when something is not going according to the plan. This short paper discusses robustness as a way to prevent the issues with uncertainty, dynamicity, and possible involvement of other (uncontrolled) agents.

Research paper thumbnail of On modeling planning problems in tabled logic programming

Current research in planning focuses mainly on so called domain independent models using the Plan... more Current research in planning focuses mainly on so called domain independent models using the Planning Domain Description Language (PDDL) as the domain modeling language. This declarative modeling approach embraces the idea of a physics-only model describing how actions change the world. However, PDDL omits information about why and when the actions should be applied to reach the goal, which significantly decreases the practical applicability of PDDL. There exist approaches such as Hierarchical Task Networks (HTN) and control rules that add this type of information to the model with the pay-off of increased efficiency but also with the downside of increased complexity and code sizes. In this paper we propose a modeling framework for planning problems based on tabled logic programming that exploits a planner module in the Picat language. This modeling framework supports structured description of world states as well as inclusion of control knowledge and heuristics in the action model. By using problems from the International Planning Competition, we experimentally demonstrate that this modeling framework achieves results comparable to planners with control rules and HTN while keeping the size of the domain model much smaller. We also show that it gives much better solving efficiency than the state-of-the-art domain-independent PDDL planners.

Research paper thumbnail of Replanning in Predictive-reactive Scheduling

Achieving optimal results in real-life production scheduling is precluded by a number of problems... more Achieving optimal results in real-life production scheduling is precluded by a number of problems. One such problem is dynamics of environments with unavailable resources (such as machine breakdowns and ill workers) and new demands (e.g. new orders) coming during the schedule execution. Traditional approach to react to unexpected events occurring on the shop floor is generating a new schedule from scratch. Complete rescheduling, however, may require excessive computation time. Moreover, the recovered schedule may deviate a lot from the ongoing schedule. Some work has focused on tackling these shortcomings, but none of the existing approaches tries to substitute jobs that cannot be executed with a set of alternative jobs. This paper reviews techniques related to predictive-reactive scheduling and suggests the future goal, which is to propose algorithms for dealing with unexpected events using the possibility of alternative processes.

Research paper thumbnail of Searching for Sequential Plans Using Tabled Logic Programming

Logic programming provides a declarative framework for modeling and solving many combinatorial pr... more Logic programming provides a declarative framework for modeling and solving many combinatorial problems. Until recently, it was not competitive with state of the art planning techniques partly due to search capabilities limited to backtracking. Recent development brought more advanced search techniques to logic programming such as tabling that simplifies implementation and exploitation of more sophisticated search algorithms. Together with rich modeling capabilities this progress brings tabled logic programing on a par with current best planners. The paper brings an initial experimental study comparing various approaches to search for sequential plans in the Picat planning module.

Research paper thumbnail of On Total-Order HTN Plan Verification with Method Preconditions – An Extension of the CYK Parsing Algorithm

Proceedings of the AAAI Conference on Artificial Intelligence

In this paper, we consider the plan verification problem for totally ordered (TO) HTN planning. T... more In this paper, we consider the plan verification problem for totally ordered (TO) HTN planning. The problem is proved to be solvable in polynomial time by recognizing its connection to the membership decision problem for context-free grammars. Currently, most HTN plan verification approaches do not have special treatments for the TO configuration, and the only one features such an optimization still relies on an exhaustive search. Hence, we will develop a new TOHTN plan verification approach in this paper by extending the standard CYK parsing algorithm which acts as the best decision procedure in general.

Research paper thumbnail of Parsing-Based Recognition of Hierarchical Plans Using the Grammar Constraint

The International FLAIRS Conference Proceedings

Plan recognition is the problem of recognizing a goal task and an agent’s plan based on the obser... more Plan recognition is the problem of recognizing a goal task and an agent’s plan based on the observed actions. Plan recognition techniques can be employed in multiagent systems, behaviour recognition, computer security, and other fields related to artificial intelligence. Hierarchical task networks (HTN) describe the decomposition hierarchy of tasks in planning problems. In HTN plan recognition, a prefix of the plan (actions observed so far) is given as an input, and the aim is to find a task that decomposes into a sequence of actions with the given prefix. In this paper, we show how the performance of parsing-based HTN plan recognition can be improved by restricting possible suffixes of the given prefix based on generalized arc consistency of a corresponding context-free grammar.

Research paper thumbnail of Multi-Agent Pathfinding on Large Maps Using Graph Pruning: This Way or That Way?

Proceedings of the 15th International Conference on Agents and Artificial Intelligence

This paper extends a study on improving the performance of reduction-based solvers for the proble... more This paper extends a study on improving the performance of reduction-based solvers for the problem of multi-agent pathfinding. The task is to navigate a set of agents in a graph without collisions. Solvers that reduce this problem to other formalisms often have issues scaling to larger instances in terms of the graph size. A previous study suggests that pruning the graph of most vertices based on a randomly chosen shortest path for each agent. In this paper, we study the effect of different choices of these paths.

Research paper thumbnail of On Heuristics for Parsing-based Verification of Hierarchical Plans with a Goal Task

Proceedings of the ... International Florida Artificial Intelligence Research Society Conference, May 4, 2022

Verification of hierarchical plans deals with the problem if a given action sequence is a valid h... more Verification of hierarchical plans deals with the problem if a given action sequence is a valid hierarchical plan -the action sequence can be obtained by decomposing a particular (goal) task using given decomposition methods. The existing parsing-based verification approach greedily composes actions until it obtains the goal task. Greediness implies that this approach also generates tasks unrelated to the goal task. In this paper, we study the use of heuristics when creating new tasks. We also ask whether the prior knowledge of the goal task improves efficiency.

Research paper thumbnail of Guiding Planning Engines by Transition-Based Domain Control Knowledge

Domain-independent planning requires only to specify planning problems in a standard language (e.... more Domain-independent planning requires only to specify planning problems in a standard language (e.g. PDDL) in order to utilise planning in some application. Despite a huge advancement in domain-independent planning, some relatively-easy problems are still challenging for existing planning engines. Such an issue can be mitigated by specifying Domain Control Knowledge (DCK) that can provide better guidance for planning engines. In this paper, we introduce transition-based DCK, inspired by Finite State Automata, that is efficient as demonstrated empirically, planner-independent (can be encoded within planning problems) and easy to specify.

Research paper thumbnail of An Ad-hoc Planner for the Mars Express Mission

Complete planning and scheduling of all spacecraft operations is a challenging area with the remo... more Complete planning and scheduling of all spacecraft operations is a challenging area with the remote agent experiment at Deep Space 1 being a pioneering system. Still the complete approach is rare in practice. For example, in the Mars Express (MEX) mission, planning and scheduling techniques are used to solve some subproblems namely scheduling command upload and data download. In this paper we describe an approach to generate a complete schedule of the spacecraft that includes planning and scheduling of science, command uplink, data downlink, maintenance, and pointing operations. The proposed solving approach was designed to plan operations on the Mars Express (MEX) mission and it was motivated by the MEX challenge at the Fourth International Competition on Knowledge Engineering for Planning and Scheduling. The method is based on incremental addition of operations to a partial schedule and modifying the time allocation of already scheduled operations to fit the newly added operation....

Research paper thumbnail of Foundations of constraint programming

Constraint programming represents Constraint programming represents one of the closest approaches... more Constraint programming represents Constraint programming represents one of the closest approaches one of the closest approaches computer science has yet made to the computer science has yet made to the Holy Grail of programming: the user Holy Grail of programming: the user states the problem, the computer states the problem, the computer solves it." solves it.

Research paper thumbnail of Minimization of useless work in resource failure recovery of workflow schedules

2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2017

Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments... more Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments with unforeseen events occurring during the execution of a schedule. Namely, in the case of a resource failure, it may be necessary to process a lot of work again, or a feasible schedule recovery may not exist at all. Moreover, the time window within which the ongoing schedule must be updated may be very short, and too timeconsuming computation of the schedule may lead to a failure of the scheduling mechanism and setback in production. Our approach in the area of predictive-reactive scheduling is to allow for substitution of tasks, which cannot be executed, with a set of alternative tasks. This paper makes use of the model of the hierarchical workflows and gives an SMT and a CSP models to recover an ongoing schedule from a resource failure with the objective to minimize the work processed in vain. The experimental analysis identified parameters for which the SMT model clearly outperform...

Research paper thumbnail of Colored Multi-Agent Path Finding: Solving Approaches

The International FLAIRS Conference Proceedings, 2021

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set ... more Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents moving in a shared environment while each agent has specified its destination. Colored MAPF generalizes MAPF by defining groups of agents that share a set of destination locations. In the paper, we evaluate several approaches to optimally solve the colored MAPF problem, namely, a method based on network flows, an extended version of conflict-based search, and two models using Boolean satisfiability. We also investigate methods for obtaining lower bounds on optimal solutions based on constraint and continuous relaxation techniques.

Research paper thumbnail of Multi-Agent Path Finding on Ozobots

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, Aug 1, 2019

Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (... more Multi-agent path finding (MAPF) is the problem to find collision-free paths for a set of agents (mobile robots) moving on a graph. There exists several abstract models describing the problem with various types of constraints. The demo presents software to evaluate the abstract models when the plans are executed on Ozobots, small mobile robots developed for teaching programming. The software allows users to design the grid-like maps, to specify initial and goal locations of robots, to generate plans using various abstract models implemented in the Picat programming language, to simulate and to visualise execution of these plans, and to translate the plans to command sequences for Ozobots.

Research paper thumbnail of Iterative Forward Search Algorithm: Combining Local Search with Maintaining Arc Consistency and a Conflict-Based Statistics

Lecture Notes in Computer Science, 2004

The paper presents an iterative forward search framework for solving constraint satisfaction and ... more The paper presents an iterative forward search framework for solving constraint satisfaction and optimization problems. This framework combines ideas of local search, namely improving a solution by local steps, with principles of depth-first search, in particular extending a partial feasible assignment towards a solution. Within this framework, we also propose and study a conflict-based statistics and explanationbased arc consistency maintenance. To show the versatility of the proposed framework, the dynamic backtracking algorithm with maintaining arc consistency is presented as a special instance of the iterative forward search framework. The presented techniques are compared on random constraint satisfaction problems and a real-life lecture timetabling problem.

Research paper thumbnail of Constraint Hierarchy Networks

Research paper thumbnail of Revisiting Constraint Models for Planning Problems

Lecture Notes in Computer Science, 2009

Planning problems deal with finding a (shortest) sequence of actions that transfer the initial st... more Planning problems deal with finding a (shortest) sequence of actions that transfer the initial state of the world into a desired state. Frequently such problems are solved by dedicated algorithms but there exist planners based on translating the planning problem into a different formalism such as constraint satisfaction or Boolean satisfiability and using a general solver for this formalism. The paper describes how to enhance existing constraint models of planning problems by using techniques such as symmetry breaking (dominance rules), singleton consistency, and lifting.

Research paper thumbnail of On Generators of Random Quasigroup Problems

Lecture Notes in Computer Science, 2006

Problems that can be sampled randomly are a good source of test suites for comparing quality of c... more Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of structured random problems that are closer to real-life problems and hence more suitable for benchmarking. In this paper, we describe in detail generators for Quasigroup Completion Problem (QCP) and Quasigroups with Holes (QWH). In particular, we study an improvement of the generator for QCP that produces a larger number of satisfiable problems by using propagation through the all-different constraint. We also re-formulate the algorithm for generating QWH that is much faster than the original generator. Finally, we provide an experimental comparison of all presented generators.

Research paper thumbnail of Constructive Negation in CLP(H)

Inclusion of negation into logic programs is considered traditionally to be painful as the incorp... more Inclusion of negation into logic programs is considered traditionally to be painful as the incorporation of full logic negation tends to super-exponen tial time complexity of the prover. Therefore the alternative approaches to negation in logic programs are studied and among them, the procedural negation as failure sounds to be the most successful and the most widely used. However, with the spread of Constraint Logic Programming (CLP), a different approach called constructive negation becomes more popular. The reasons for acceptance of constructive negation are the preservation of the advantages of the negation as failure, i.e., efficiency and handling special features of the language, and, at the same time, while removing the main drawbacks, i.e., handling ground negative subgoals and usage as a test only. In this paper we present a constructive approach to negation in logic programs. We concentrate on implementation aspects of constructive negation here, i.e., on the design of CLP...

Research paper thumbnail of Constructive Negation and Constraints

Inclusion of negation into logic programs is considered traditionally to be painful as the incorp... more Inclusion of negation into logic programs is considered traditionally to be painful as the incorporation of full logic negation tends to super-exponen tial time complexity of the prover. Therefore the alternative approaches to negation in logic programs are studied and among them, the procedural negation as failure sounds to be the most successful and the most widely used. However, Constraint Logic Programming (CLP) is offering a different approach called constructive negation, that is becoming more popular. In this paper we present a constructive approach to negation in logic programs. We concentrate on implementatio n aspects of constructive negation here, i.e., on the design of CLP( H) system, where H is the Herbrand Universe.