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Software

Multiagent decision process toolbox

The Multiagent decision process (MADP) Toolbox is a free C++ software toolbox for scientific research in decision-theoretic planning and learning in multiagent systems (MASs). It is jointly developed by Frans Oliehoek and me. We use the term MADP to refer to a collection of mathematical models for multiagent planning: multiagent Markov decision processes (MMDPs), decentralized MDPs (Dec-MDPs), decentralized partially observable MDPs (Dec-POMDPs), partially observable stochastic games (POSGs), etc.

The toolbox is designed to be rather general, potentially providing support for all these models, although so far most effort has been put in planning algorithms for discrete Dec-POMDPs. It provides classes modeling the basic data types of MADPs (e.g., action, observations, etc.) as well as derived types for planning (observation histories, policies, etc.). It also provides base classes for planning algorithms and includes several applications using the provided functionality. For instance, applications that use JESP or brute-force search to solve .dpomdp files for a particular planning horizon. In this way, Dec-POMDPs can be solved directly from the command line. Furthermore, several utility applications are provided, for instance one which empirically determines a joint policy's control quality by simulation.

Its homepage, from which code and documentation are available.

Perseus approximate POMDP solving software

Matlab parser for Tony's POMDP file format

Perseus approximate POMDP algorithm implementation

POMDPs with continuous spaces

Josep Porta cleaned up and reimplemented the code we used for the JMLR2006 paper, it's available at his webpage.