AgentSpeak+: AgentSpeak with probabilistic planning

AgentSpeak is a logic-based programming language, based on the Belief-Desire-Intention (BDI) paradigm, suitable for building complex agent-based systems. To limit the computational complexity, agents in AgentSpeak rely on a plan library to reduce the planning problem to the much simpler problem of plan selection. However, such a plan library is often inadequate when an agent is situated in an uncertain environment. In this paper, we propose the AgentSpeak framework, which extends AgentSpeak with a mechanism for probabilistic planning. The beliefs of an AgentSpeak agent are represented using epistemic states to allow an agent to reason about its uncertain observations and the uncertain effects of its actions. Each epistemic state consists of a POMDP, used to encode the agent’s knowledge of the environment, and its associated probability distribution (or belief state). In addition, the POMDP is used to select the optimal actions for achieving a given goal, even when facing uncertainty.

[1]  Michael Wooldridge,et al.  Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology) , 2007 .

[2]  Michael Luck,et al.  Declarative planning in procedural agent architectures , 2013, Expert Syst. Appl..

[3]  Weiru Liu,et al.  CAN(PLAN)+: Extending the Operational Semantics of the BDI Architecture to deal with Uncertain Information , 2014, UAI.

[4]  Lluis Godo,et al.  A graded BDI agent model to represent and reason about preferences , 2011, Artif. Intell..

[5]  Anand S. Rao,et al.  An Abstract Architecture for Rational Agents , 1992, KR.

[6]  Winfried Lamersdorf,et al.  Jadex: Implementing a BDI-Infrastructure for JADE Agents , 2003 .

[7]  R. Bellman.  A Markovian Decision Process , 1957 .

[8]  Lin Padgham,et al.  A BDI agent programming language with failure handling, declarative goals, and planning , 2011, Autonomous Agents and Multi-Agent Systems.

[9]  Simon Parsons,et al.  On using degrees of belief in BDI agents , 2004 .

[10]  Weiru Liu,et al.  A framework for managing uncertain inputs: An axiomization of rewarding , 2011, Int. J. Approx. Reason..

[11]  Kristian G. Olesen,et al.  HUGIN - A Shell for Building Bayesian Belief Universes for Expert Systems , 1989, IJCAI.

[12]  John Langford,et al.  Probabilistic Planning in the Graphplan Framework , 1999, ECP.

[13]  Nicholas R. Jennings,et al.  Agent-based control systems , 2003 .

[14]  Gerardo I. Simari.  On Approximating the Best Decision for an Autonomous Agent , 2004 .

[15]  Weiru Liu,et al.  Incorporating PGMs into a BDI Architecture , 2013, PRIMA.

[16]  A. S. Roa,et al.  AgentSpeak(L): BDI agents speak out in a logical computable language , 1996 .

[17]  Simon Parsons,et al.  On representing planning domains under uncertainty , 2010 .

[18]  Leslie Pack Kaelbling,et al.  Planning and Acting in Partially Observable Stochastic Domains , 1998, Artif. Intell..

[19]  Michael Wooldridge,et al.  On Partially Observable MDPs and BDI Models , 2002, Foundations and Applications of Multi-Agent Systems.

[20]  Eric A. Hansen,et al.  Solving POMDPs by Searching in Policy Space , 1998, UAI.