richard belew - Academia.edu (original) (raw)
Papers by richard belew
. The traditional explanation of delayed maturation age, as part of an evolved life history, focu... more . The traditional explanation of delayed maturation age, as part of an evolved life history, focuses on the increased costs of juvenile mortality due to early maturation. Prior quantitative models of these trade-offs, however, have addressed only morphological phenotypic traits, such as body size. We argue that the development of behavioral skills prior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining the trade-off for optimal age at maturity. Empirical support for this hypothesis from animal field studies is abundant. This paper provides further evidence drawn from simulation experiments. "Latent Energy Environments" (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolved according to a type of genetic algorithm. An advantage of this artificial world is that it becomes possible to discount all non-behavioral costs of ear...
Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations... more Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations with coupled fitness landscapes. In this paper we consider "competitive coevolution, " in which the fitness of an individual in a "host" population is based on direct competition with individual(s) from a "parasite " population. Competitive co-evolution is applied to three game-learning problems: Tic-Tac-Toe (TTT), Nim and a small version of Go. Two new techniques in competitive co-evolution are explored. "Competitive fitness sharing" changes the way fitness is measured, and "shared sampling" alters the way parasites are chosen for testing hosts. Experiments using TTT and Nim show a substantial improvement in performance when these methods are used. Preliminary results using co-evolution for the discovery of cellular automata rules for playing Go are presented. 1 Introduction Co-evolution refers to the simultaneous evolution of two or mo...
Nonconvex Optimization and Its Applications, 2000
Proceedings of the conference on Office information systems -, 1990
Journal of Chemical Information and Modeling, 2007
Artificial Life and Robotics, 2000
Description/Abstract One interesting issue in artificial intelligence (Al) currently is the relat... more Description/Abstract One interesting issue in artificial intelligence (Al) currently is the relative merits of, and relationship between, the symbolic and connectionist approaches to intelligent systems building. The performance of more-traditional symbolic systems has been striking ...
Proceedings of the Swedish Conference on Connectionism, Mar 1, 1995
Information retrieval di ers signi cantly from function approximation in that the goal is for the... more Information retrieval di ers signi cantly from function approximation in that the goal is for the system to achieve the same ranking function of documents relative to queries as the user: the outputs of the system relative to one another must be in the proper order. We hypothesize that a particular rank-order statistic, Guttman's point alienation, is the proper objective function for such a system, and demonstrate its e cacy by using it to nd the optimal combination of retrieval experts. In application to a commercial retrieval system, the ...
The UCSD Department of Computer Science and Engineering recently submitted a proposal for large-s... more The UCSD Department of Computer Science and Engineering recently submitted a proposal for large-scale Research Infrastructure funding to the National Science Foundation. The theme of the proposal is the ���Active Web���, a next-generation World Wide Web premised on the support for active content, content that is rich in multimedia and references to other other objects, and for mobile agents, programs that can move about and execute on remote servers, carrying out requests at a distance on behalf of users. These ...
Adaptive Behavior, 1995
The traditional explanation of delayed maturation age, as part of an evolved life history, focuse... more The traditional explanation of delayed maturation age, as part of an evolved life history, focuses on the increased costs of juvenile mortality due to early maturation. Prior quantitative models of these trade-offs, however, have addressed only morphological phenotypic traits, such as body size. We argue that the development of behavioral skills prior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining the trade-off for optimal age at maturity. Empirical support for this hypothesis from animal field studies is abundant. This article provides further evidence drawn from simulation experiments. Latent energy environments (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolve according to a type of genetic algorithm. An advantage of this artificial world is that it becomes possible to discount all nonbehavioral costs of early maturity in...
Hierarchies are a natural way for people to organize information, as reflected by the common use ... more Hierarchies are a natural way for people to organize information, as reflected by the common use of ``broader/narrower'''' term relation in keyword thesauri. However, different people and organizations tend to construct different conceptual hierarchies (e.g., contrast Yahoo! with the UseNet news hierarchy), and while there are often significant commonalities it is in general quite difficult to fully reconcile them. We are particularly interested in the problem of ``docking'''' a narrower, more focused and refined topical hierarchy into a broader one, and describe two algorithms for accomplishing this task. The first matches hierarchies based on a bipartite matching algorithm of (textual) features of nodes without consideration of their hierarchic organization, and the second is based on an attributed tree matching algorithm which uses both hierarchic structure and node features. We present experimental results showing the performance of both algorithm...
Journal of chemical information and modeling, Aug 22, 2016
We describe ADChemCast, a method for using results from virtual screening to create a richer repr... more We describe ADChemCast, a method for using results from virtual screening to create a richer representation of a target binding site, which may be used to improve ranking of compounds and characterize the determinants of ligand-receptor specificity. ADChemCast clusters docked conformations of ligands based on shared pairwise receptor-ligand interactions within chemically similar structural fragments, building a set of attributes characteristic of binders and nonbinders. Machine learning is then used to build rules from the most informational attributes for use in reranking of compounds. In this report, we use ADChemCast to improve the ranking of compounds in 11 diverse proteins from the Database of Useful Decoys-Enhanced (DUD-E) and demonstrate the utility of the method for characterizing relevant binding attributes in HIV reverse transcriptase.
. The traditional explanation of delayed maturation age, as part of an evolved life history, focu... more . The traditional explanation of delayed maturation age, as part of an evolved life history, focuses on the increased costs of juvenile mortality due to early maturation. Prior quantitative models of these trade-offs, however, have addressed only morphological phenotypic traits, such as body size. We argue that the development of behavioral skills prior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining the trade-off for optimal age at maturity. Empirical support for this hypothesis from animal field studies is abundant. This paper provides further evidence drawn from simulation experiments. "Latent Energy Environments" (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolved according to a type of genetic algorithm. An advantage of this artificial world is that it becomes possible to discount all non-behavioral costs of ear...
Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations... more Co-evolution refers to the simultaneous evolution of two or more genetically distinct populations with coupled fitness landscapes. In this paper we consider "competitive coevolution, " in which the fitness of an individual in a "host" population is based on direct competition with individual(s) from a "parasite " population. Competitive co-evolution is applied to three game-learning problems: Tic-Tac-Toe (TTT), Nim and a small version of Go. Two new techniques in competitive co-evolution are explored. "Competitive fitness sharing" changes the way fitness is measured, and "shared sampling" alters the way parasites are chosen for testing hosts. Experiments using TTT and Nim show a substantial improvement in performance when these methods are used. Preliminary results using co-evolution for the discovery of cellular automata rules for playing Go are presented. 1 Introduction Co-evolution refers to the simultaneous evolution of two or mo...
Nonconvex Optimization and Its Applications, 2000
Proceedings of the conference on Office information systems -, 1990
Journal of Chemical Information and Modeling, 2007
Artificial Life and Robotics, 2000
Description/Abstract One interesting issue in artificial intelligence (Al) currently is the relat... more Description/Abstract One interesting issue in artificial intelligence (Al) currently is the relative merits of, and relationship between, the symbolic and connectionist approaches to intelligent systems building. The performance of more-traditional symbolic systems has been striking ...
Proceedings of the Swedish Conference on Connectionism, Mar 1, 1995
Information retrieval di ers signi cantly from function approximation in that the goal is for the... more Information retrieval di ers signi cantly from function approximation in that the goal is for the system to achieve the same ranking function of documents relative to queries as the user: the outputs of the system relative to one another must be in the proper order. We hypothesize that a particular rank-order statistic, Guttman's point alienation, is the proper objective function for such a system, and demonstrate its e cacy by using it to nd the optimal combination of retrieval experts. In application to a commercial retrieval system, the ...
The UCSD Department of Computer Science and Engineering recently submitted a proposal for large-s... more The UCSD Department of Computer Science and Engineering recently submitted a proposal for large-scale Research Infrastructure funding to the National Science Foundation. The theme of the proposal is the ���Active Web���, a next-generation World Wide Web premised on the support for active content, content that is rich in multimedia and references to other other objects, and for mobile agents, programs that can move about and execute on remote servers, carrying out requests at a distance on behalf of users. These ...
Adaptive Behavior, 1995
The traditional explanation of delayed maturation age, as part of an evolved life history, focuse... more The traditional explanation of delayed maturation age, as part of an evolved life history, focuses on the increased costs of juvenile mortality due to early maturation. Prior quantitative models of these trade-offs, however, have addressed only morphological phenotypic traits, such as body size. We argue that the development of behavioral skills prior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining the trade-off for optimal age at maturity. Empirical support for this hypothesis from animal field studies is abundant. This article provides further evidence drawn from simulation experiments. Latent energy environments (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolve according to a type of genetic algorithm. An advantage of this artificial world is that it becomes possible to discount all nonbehavioral costs of early maturity in...
Hierarchies are a natural way for people to organize information, as reflected by the common use ... more Hierarchies are a natural way for people to organize information, as reflected by the common use of ``broader/narrower'''' term relation in keyword thesauri. However, different people and organizations tend to construct different conceptual hierarchies (e.g., contrast Yahoo! with the UseNet news hierarchy), and while there are often significant commonalities it is in general quite difficult to fully reconcile them. We are particularly interested in the problem of ``docking'''' a narrower, more focused and refined topical hierarchy into a broader one, and describe two algorithms for accomplishing this task. The first matches hierarchies based on a bipartite matching algorithm of (textual) features of nodes without consideration of their hierarchic organization, and the second is based on an attributed tree matching algorithm which uses both hierarchic structure and node features. We present experimental results showing the performance of both algorithm...
Journal of chemical information and modeling, Aug 22, 2016
We describe ADChemCast, a method for using results from virtual screening to create a richer repr... more We describe ADChemCast, a method for using results from virtual screening to create a richer representation of a target binding site, which may be used to improve ranking of compounds and characterize the determinants of ligand-receptor specificity. ADChemCast clusters docked conformations of ligands based on shared pairwise receptor-ligand interactions within chemically similar structural fragments, building a set of attributes characteristic of binders and nonbinders. Machine learning is then used to build rules from the most informational attributes for use in reranking of compounds. In this report, we use ADChemCast to improve the ranking of compounds in 11 diverse proteins from the Database of Useful Decoys-Enhanced (DUD-E) and demonstrate the utility of the method for characterizing relevant binding attributes in HIV reverse transcriptase.