Probabilistic Selection in AgentSpeak(L)

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 u...

Agent programming with priorities and deadlines

We present AgentSpeak(RT), a real-time BDI agent programming language based on AgentSpeak(L). AgentSpeak(RT) extends AgentSpeak intentions with deadlines which specify the time by which the agent should respond to an event, and priorities which specify the relative importance of responding to a particular event. The AgentSpeak(RT) interpreter commits to a priority-maximal set of intentions: a s...

Probabilistic Planning in AgentSpeak using the POMDP framework

Efficient Intention Selection in BDI Agents via Decision-Theoretic Task Scheduling

This paper shows how to use a decision-theoretic task scheduler in order to automatically generate efficient intention selection functions for BDI agent-oriented programming languages. We concentrate here on the particular extensions to a known BDI language called AgentSpeak(L) and its interpreter which were necessary so that the integration with a task scheduler was possible. The proposed lang...

CASO: a framework for dealing with objectives in a constraint-based extension to AgentSpeak(L)

Incorporating constraints into a reactive BDI agent programming language can lead to better expressive capabilities as well as more efficient computation (in some instances). More interestingly, the use of constraint-based representations can make it possible to deal with explicit agent objectives (as distinct from agent goals) that express the things that an agent may seek to optimize at any g...