An operational semantics for the goal life-cycle in BDI agents

Harland, James; Morley, David N.; Thangarajah, John; Yorke-Smith, Neil

doi:10.1007/s10458-013-9238-9

Cited by 23 publications

(38 citation statements)

References 20 publications

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“…8, between the goal and plan levels there are the BDI logics or more commonly a goal automaton [2,3] which handles the goal life-cycle. This life-cycle usually starts with the adoption of the goal and includes the choice and execution of plans.…”

Section: Executionmentioning

confidence: 99%

“…The aspect of the Goal-Plan Separation that handles goal reasoning is situated at what Harland et al [3] and Thangarajah et al in earlier works [4,13] call agent deliberation level. This is where agent goals are considered, which constitutes the point where goals start their life-cycle.…”

Section: Related Workmentioning

confidence: 99%

“…In more practical approaches, automata are used to handle the life-cycle of goals from their adoption to the appropriate plan selection and execution [2,3]. The purpose of an agent is usually to act on the environment, which is done through its plans.…”

Section: Introductionmentioning

confidence: 99%

“…The purpose of an agent is usually to act on the environment, which is done through its plans. Actions can involve the use of actuators, but they also cover the sending of messages 3 . However, in practice, various works [3,4] and programming frameworks (Jason [5], Jadex [6] etc.)…”

Section: Introductionmentioning

confidence: 99%

“…Actions can involve the use of actuators, but they also cover the sending of messages 3 . However, in practice, various works [3,4] and programming frameworks (Jason [5], Jadex [6] etc.) employ a model where plans can also adopt new goals, often termed sub-goals.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Keeping a Clear Separation between Goals and Plans

Caval

Seghrouchni

Taillibert

2014

Engineering Multi-Agent Systems

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Abstract. Many approaches to BDI agent modeling permit the agent developers to interweave the levels of plans and goals. This is possible through the adoption of new goals inside plans. These goals will have plans of their own, and the definition can extend on many levels. From a software development point of view, the resulting complexity can render the agents' behavior difficult to trace, due to the combination of elements from different abstraction levels, i.e., actions and goal adoptions. This has a negative effect on the development process when designing and debugging agents. In this paper we propose a change of approach that aims to provide a more comprehensible agent model with benefits for the ease of engineering and the fault tolerance of agent systems. This is achieved by imposing a clear separation between the reasoning and the acting levels of the agent. The use of goal adoptions and actions on the environment inside the same plan is therefore forbidden. The approach is illustrated using two theoretical scenarios as well as an agent-based maritime patrol application. We argue that by constraining the agent model we gain in clarity and traceability therefore benefiting the development process and encouraging the adoption of agent-based techniques in industrial contexts.

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Section: Executionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Keeping a Clear Separation between Goals and Plans

Caval

Seghrouchni

Taillibert

2014

Engineering Multi-Agent Systems

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A Multi-level Approach to the Formal Semantics of Agent Societies

Panisson

Bordini

Costa

2020

Intelligent Systems

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Implementing Durative Actions with Failure Detection in Gwendolen

Stringer

Cardoso

Dixon

et al. 2022

Engineering Multi-Agent Systems

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We present an extension of the semantics for action execution in the Gwendolen BDI programming language. This extension firstly explicitly assumes that actions have durations and, moreover, that the reasoning cycle of the agent can not be stopped while such an action is executing but needs to continue in order to monitor for important external events. Secondly, the extension assumes that actions may often fail and this needs to be detected. This forms part of a larger project to develop a framework plan/action adaptation within BDI agents in order to enable long-term autonomy. We have implemented the extension and demonstrate its operation in a simple case study.

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An operational semantics for the goal life-cycle in BDI agents

Cited by 23 publications

References 20 publications

Keeping a Clear Separation between Goals and Plans

Keeping a Clear Separation between Goals and Plans

A Multi-level Approach to the Formal Semantics of Agent Societies

Implementing Durative Actions with Failure Detection in Gwendolen

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