A Hybrid POMDP-BDI Agent Architecture with Online Stochastic Planning and Desires with Changing Intensity Levels

Rens, Gavin; Meyer, Thomas

doi:10.1007/978-3-319-27947-3_1

Cited by 1 publication

(4 citation statements)

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“…In previous work (Rens and Meyer, 2015), we argued that maintenance goals like avoiding moist areas (or collecting soil samples) should rather be viewed as a preference and modeled as a POMDP reward function. And specific tasks to complete (like collecting gas or keeping its battery charged) should be modeled as BDI desires.…”

Section: Discussionmentioning

confidence: 99%

“…A Hybrid POMDP-BDI (HPB) agent (Rens and Meyer, 2015) maintains (i) a belief state which is periodically updated, (ii) a mapping from goals to numbers representing the level of desire to achieve the goals, and (iii) the current set of intentions, the goals with the highest desire levels (roughly speaking). As the agent acts, its desire levels are updated and it may consider choosing new intentions and discard others based on new desire levels.…”

Section: Preliminariesmentioning

confidence: 99%

“…The Hybrid POMDP-BDI agent architecture (or HPB architecture, for short) has recently been introduced (Rens and Meyer, 2015). It combines the advantages of POMDP theoretic reasoning and the potentially sophisticated means-ends reasoning of BDI theory in a coherent agent architecture.…”

Section: Introductionmentioning

confidence: 99%

“…This article serves to introduce two significant extensions to the first iteration (Rens and Meyer, 2015) of the HPB architecture. The first extension allows for multiple intentions to be pursued simultaneously, instead of one at a time.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching

Rens

Moodley

2017

Cognitive Systems Research

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This article presents an agent architecture for controlling an autonomous agent in stochastic environments. The architecture combines the partially observable Markov decision process (POMDP) model with the belief-desire-intention (BDI) framework. The Hybrid POMDP-BDI agent architecture takes the best features from the two approaches, that is, the online generation of reward-maximizing courses of action from POMDP theory, and sophisticated multiple goal management from BDI theory. We introduce the advances made since the introduction of the basic architecture, including (i) the ability to pursue multiple goals simultaneously and (ii) a plan library for storing pre-written plans and for storing recently generated plans for future reuse. A version of the architecture without the plan library is implemented and is evaluated using simulations. The results of the simulation experiments indicate that the approach is feasible.

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Section: Discussionmentioning

confidence: 99%

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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