Autonomous Agents and Multi-Agent Systems

, Volume 29, Issue 4, pp 569–620 | Cite as

A logic of intention and action for regular BDI agents based on bisimulation of agent programs

  • Wayne WobckeEmail author


We address the problem of providing a computationally grounded semantics for belief, desire, intention (BDI) agents that explicitly relates intention to action, using as a basis for this connection a notion of bisimulation for agent programs. We first define regular BDI agents, a class of BDI agents inspired by the procedural reasoning system architecture, under the restriction that agent programs are representable as regular expressions. The operational semantics of regular agent programs is formalized using agent program execution graphs, an extension of the process graphs used to formalize regular processes. An agent’s executed program represents an attempt to perform an intended plan and can include branches for both successful execution and the failure of action attempts; intended execution paths are defined in terms of successful executions, and intentions in terms of future successfully executed agent programs. We present Agent Dynamic Logic (\(\mathsf {ADL}\)), a logic of intention and action that faithfully represents the operational semantics of regular BDI agents. \(\mathsf {ADL}\) is a logic in the spirit of BDI logic but also includes the dynamic logic of actions and a reduction of the logic of intention to the logics of action and time. A main contribution of the paper is a completeness result for a subclass of finite \(\mathsf {ADL}\) theories with explicit representations of agent plans.


Rational agents Dynamic logic Temporal logic  Bisimulation 



This work was initially funded by an Australian Research Council Discovery Project Grant. Discussions with Krystian Ji have helped greatly in clarifying the main issues addressed in this paper. Thanks also to participants of the Otago Workshop on Logic and Multi-Agent Systems, the Decision Systems Laboratory at the University of Wollongong, the AAAI 2007 Stanford Spring Symposium on Intentions in Intelligent Systems, and two Australian Knowledge Representation Conventicles, for feedback on earlier versions of these ideas, and to the anonymous reviewers for comments on an earlier version of this paper.


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© The Author(s) 2014

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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