Download all versions of burlap JAR files with all dependencies
burlap from group edu.brown.cs.burlap (version 3.0.1)
The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and
development of single or multi-agent planning and learning algorithms and domains to accompany them. The library
uses a highly flexible state/observation representation where you define states with your own Java classes, enabling
support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search
planning to value-function-based stochastic planning and learning algorithms.
Artifact burlap
Group edu.brown.cs.burlap
Version 3.0.1
Last update 03. August 2016
Tags: burlap single development range domains state states from where function forward search value highly algorithms classic else classes define continuous with support umbc observation your learning code flexible agent stochastic that enabling anything discrete planning representation them library multi relational uses accompany brown java reinforcement based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
Group edu.brown.cs.burlap
Version 3.0.1
Last update 03. August 2016
Tags: burlap single development range domains state states from where function forward search value highly algorithms classic else classes define continuous with support umbc observation your learning code flexible agent stochastic that enabling anything discrete planning representation them library multi relational uses accompany brown java reinforcement based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
burlap from group edu.brown.cs.burlap (version 3.0.0)
The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and
development of single or multi-agent planning and learning algorithms and domains to accompany them. The library
uses a highly flexible state/observation representation where you define states with your own Java classes, enabling
support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search
planning to value-function-based stochastic planning and learning algorithms.
Artifact burlap
Group edu.brown.cs.burlap
Version 3.0.0
Last update 18. June 2016
Tags: burlap single development range domains state states from where function forward search value highly algorithms classic else classes define continuous with support umbc observation your learning code flexible agent stochastic that enabling anything discrete planning representation them library multi relational uses accompany brown java reinforcement based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
Group edu.brown.cs.burlap
Version 3.0.0
Last update 18. June 2016
Tags: burlap single development range domains state states from where function forward search value highly algorithms classic else classes define continuous with support umbc observation your learning code flexible agent stochastic that enabling anything discrete planning representation them library multi relational uses accompany brown java reinforcement based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
burlap from group edu.brown.cs.burlap (version 2.1.2)
The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and
development of single or multi-agent planning and learning algorithms and domains to accompany them. The library
uses a highly flexible state/observation representation where you define states with your own Java classes, enabling
support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search
planning to value-function-based stochastic planning and learning algorithms.
Artifact burlap
Group edu.brown.cs.burlap
Version 2.1.2
Last update 18. June 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
Group edu.brown.cs.burlap
Version 2.1.2
Last update 18. June 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
burlap from group edu.brown.cs.burlap (version 2.1.1)
The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and
development of single or multi-agent planning and learning algorithms and domains to accompany them. The library
uses a highly flexible state/observation representation where you define states with your own Java classes, enabling
support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search
planning to value-function-based stochastic planning and learning algorithms.
Artifact burlap
Group edu.brown.cs.burlap
Version 2.1.1
Last update 30. April 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
Group edu.brown.cs.burlap
Version 2.1.1
Last update 30. April 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
burlap from group edu.brown.cs.burlap (version 2.1.0)
The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and
development of single or multi-agent planning and learning algorithms and domains to accompany them. The library
uses a highly flexible state/observation representation where you define states with your own Java classes, enabling
support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search
planning to value-function-based stochastic planning and learning algorithms.
Artifact burlap
Group edu.brown.cs.burlap
Version 2.1.0
Last update 25. March 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
Group edu.brown.cs.burlap
Version 2.1.0
Last update 25. March 2016
Tags: single domains supports function visualization tools forward search oriented value algorithms continuous such code wide agent default planning representation them multi included reinforcement burlap range development common state states object from analysis performance various implement types forms classic umbc rich your problem learning framework stochastic including discrete relational library java brown accompany also based
Organization not specified
URL http://burlap.cs.brown.edu
License Apache 2.0
Dependencies amount 9
Dependencies commons-math3, ejml, jcommon, jfreechart, joptimizer, junit, log4j, snakeyaml, jopt-simple,
There are maybe transitive dependencies!
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