Esra Erdem | Sabanci University (original) (raw)

Papers by Esra Erdem

For a finite state automaton, a synchronizing sequence is an input sequence that takes all the st... more For a finite state automaton, a synchronizing sequence is an input sequence that takes all the states to the same state. Checking the existence of a synchronizing sequence and finding a synchronizing sequence, if one exists, can be performed in polynomial time. However, the problem of finding a shortest synchronizing sequence is known to be NP-hard. In this work, the usefulness of Answer Set Programming to solve this optimization problem is investigated, in comparison with brute-force algorithms and SAT-based approaches.

Pathfinding for a single agent is the problem of planning a route from an initial location to a g... more Pathfinding for a single agent is the problem of planning a route from an initial location to a goal location in an environment, going around obstacles. Pathfinding for multiple agents also aims to plan such routes for each agent, subject to different constraints, such as restrictions on the length of each path, no intersection of paths/plans, no crossing/meeting each other. It also has variations for finding optimal solutions with respect to the maximum path length or the sum of plan lengths. These problems are important for many real-life applications, such as motion planning, vehicle routing, environmental monitoring, patrolling, computer games. We evaluate the applicability of Answer Set Programming to solve variations of multi-agent pathfinding problems, by experiments with randomly generated problem instances on a grid, on a real-world road network, and on a real computer game terrain.

Pathfinding for a single agent is the problem of planning a route from an initial location to a g... more Pathfinding for a single agent is the problem of planning a route from an initial location to a goal location in an environment, going around obstacles. Pathfinding for multiple agents also aims to plan such routes for each agent, subject to different constraints, such as restrictions on the length of each path or on the total length of paths, no self-intersecting paths, no intersection of paths/plans, no crossing/meeting each other. It also has variations for finding optimal solutions, e.g., with respect to the maximum path length, or the sum of plan lengths. These problems are important for many real-life applications, such as motion planning, vehicle routing, environmental monitoring, patrolling, computer games. Motivated by such applications, we introduce a formal framework that is general enough to address all these problems: we use the expressive high-level representation formalism and efficient solvers of the declarative programming paradigm Answer Set Programming. We also introduce heuristics to improve the computational efficiency and/or solution quality. We show the applicability and usefulness of our framework by experiments, with randomly generated problem instances on a grid, on a real-world road network, and on a real computer game terrain.

We introduce a new method for integrating relevant parts of knowledge extracted from biomedical o... more We introduce a new method for integrating relevant parts of knowledge extracted from biomedical ontologies and answering complex queries related to drug safety and discovery, using Semantic Web technologies and answer set programming. The applicability of this method is illustrated in detail on some parts of existing biomedical ontologies. Its effectiveness is demonstrated by computing an answer to a real-world biomedical query that requires the integration of NCBI Entrez Gene and the Gene Ontology.

Non-Monotonic Reasoning, Aug 1, 2008

For many years now, formalisms rooted in the research area of Nonmonotonic Reasoning have been us... more For many years now, formalisms rooted in the research area of Nonmonotonic Reasoning have been used as the theoretical foundation for declarative programming paradigms. These programming paradigms provide expressive languages to represent nonmonotonic concepts besides other knowledge, and systems that are implemented to automate nonmonotonic reasoning. For instance, one of the most successful of such paradigms is Answer Set Programming.

ABSTRACT This paper presents ReAct!, an interactive educational tool for artificial intelligence ... more ABSTRACT This paper presents ReAct!, an interactive educational tool for artificial intelligence (AI) planning for robotics. ReAct! enables students to describe robots' actions and change in dynamic domains without first having to know about the syntactic and semantic details of the underlying formalism, and to solve planning problems using state-of-the-art reasoners without having to know about their input/output language or usage. In particular, ReAct! can be used to represent sophisticated dynamic domains that feature concurrency, indirect effects of actions, and state/transition constraints. ReAct! also allows the embedding of externally defined calculations (e.g., checking for collision-free continuous trajectories) into domain representations of hybrid domains that require a tight integration of (discrete) high-level reasoning with (continuous) geometric reasoning. ReAct! also allows students to solve planning problems that involve complex temporal goals. This broad applicability, and the intelligent interactive user interface, mean that students can work on interesting and challenging domains, ranging from service robotics to cognitive factories, leading to hands-on robotic applications. The efficacy of ReAct! was evaluated from three different points of view: 1) the course outcomes that demonstrate its utility in achieving the learning objectives of a research-oriented cognitive robotics course; 2) the user friendliness and usefulness of ReAct! for students, as evaluated by quantitative student surveys; and 3) instructors' experience of teaching the course either with or without ReAct!.

We generalize a theorem by François Fages that describes the relationship between the completion ... more We generalize a theorem by François Fages that describes the relationship between the completion semantics and the answer set semantics for logic programs with negation as failure. The study of this relationship is important in connection with the emergence of answer set programming. Whenever the two semantics are equivalent, answer sets can be computed by a satisfiability solver, and the use of answer set solvers such as smodels and dlv is unnecessary. A logic programming representation of the blocks world due to Ilkka Niemelä is discussed as an example.

ABSTRACT We introduce a novel method to find optimal plans for multiple teams of robots through a... more ABSTRACT We introduce a novel method to find optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We introduce a novel method to solve this problem using state-of-the-art SAT solvers and ASP solvers. We show applicability and usefulness of our approach by experiments on various scenarios of cognitive factories.

Özetçe -Bu makalede robotlardan oluşan birden fazla takım için, bir aracı yardımı ile, eniyileşti... more Özetçe -Bu makalede robotlardan oluşan birden fazla takım için, bir aracı yardımı ile, eniyileştirilmiş planları bulmak amacıyla geliştirdigimiz yöntemler açıklanmaktadır. Bu problemde, her takımın kendine ait çalışma alanında tamamlaması gereken görevleri vardır ve takımlar arası robot degişimi yapılabilmektedir. Ayrıca takımlarşu kısıtları göz önünde bulundurmaktadırlar: 1) takımlar (ve aracı) birbirlerinin çalışma alanı ya da görevleri hakkında bilgi sahibi degildirler (örn. gizlilik nedeniyle); 2) her takım ya robot ödünç verebilir ya da ödünç alabilir, ama ikisini birden yapamaz (örn. robotların çalışma alanları arasında taşınmaları ve ayarlanmaları genelde zor ve masraflıdır). Bu problemi çözmek için önerdigimiz yöntem, güncel SAT çözücülerini ve çözüm kümesi programlama (ASP) çözücülerini kullanmaktır. Yaklaşımımızın uygulanabilirligi ve kullanışlılıgı bilişsel fabrikalar üzerinde çeşitli senaryolarla yaptıgımız deneylerle gösterilmiştir.

Pathfinding for a single agent is the problem of planning a route from an initial location to a g... more Pathfinding for a single agent is the problem of planning a route from an initial location to a goal location in an environment, going around obstacles. Pathfinding for multiple agents also aims to plan such routes for each agent, subject to different constraints, such as restrictions on the length of each path or on the total length of paths, no self-intersecting paths, no intersection of paths/plans, no crossing/meeting each other. It also has variations for finding optimal solutions, e.g., with respect to the maximum path length, or the sum of plan lengths. These problems are important for many real-life applications, such as motion planning, vehicle routing, environmental monitoring, patrolling, computer games. Motivated by such applications, we introduce a formal framework that is general enough to address all these problems: we use the expressive high-level representation formalism and efficient solvers of the declarative programming paradigm Answer Set Programming. We also introduce heuristics to improve the computational efficiency and/or solution quality. We show the applicability and usefulness of our framework by experiments, with randomly generated problem instances on a grid, on a real-world road network, and on a real computer game terrain.

Non-Monotonic Reasoning, Aug 1, 2008