A temporal modelling environment for internally grounded beliefs, desires and intentions

Jonker, Catholijn M.; Treur, Jan; Wijngaards, Wouter C. A.

doi:10.1016/s1389-0417(03)00004-4

Cited by 32 publications

(37 citation statements)

References 16 publications

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“…However, goal and intention concepts could also be considered explicitly by adding them to our ontology in order to get more transparency. However, this will add no essential expressivity, as they would be a renaming of already available complex expressions over our memory states; see also (Jonker, Treur, and Vries, 2002). In future work it will be investigated, which alternative or additional attitudes of agents could be included into the internal framework in order to more transparently represent certain specific types of complex behavior of an agent.…”

Section: Discussionmentioning

confidence: 99%

Formal modeling and analysis of cognitive agent behavior

Sharpanskykh

Treur

2007

Cogn Process

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Section: Discussionmentioning

confidence: 99%

Formal modeling and analysis of cognitive agent behavior

Sharpanskykh

Treur

2007

Cogn Process

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“…This section defines more precisely the temporal relation •→ → within the LEADSTO language (Jonker, Treur and Wijngaards, 2003;Bosse, Jonker, Meij, and Treur, 2007) that is used as a vehicle to formally specify the temporal relations of the developed BDImodel. This relation is defined in terms of its semantics.…”

Section: States Trajectories and 'Leads To' Relationsmentioning

confidence: 99%

“…One sort of these agent models are BDI-models describing agents in terms of internal state properties such as Beliefs, Desires and Intentions (e.g., Rao and Georgeff, 1991;Jonker, Treur and Wijngaards, 2003). In (Jonker, Snoep, Treur, Westerhoff, and Wijngaards, 2002) the BDI-modelling approach is used to identify and analyse steady states within the cell in relation to environmental circumstances.…”

Section: Introductionmentioning

confidence: 99%

BDI-modelling of complex intracellular dynamics

Jonker

Snoep

Treur

et al. 2008

Journal of Theoretical Biology

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A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalised BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as Beliefs, Desires and Intentions, are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.

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“…For formal specification of the properties, the Temporal Trace Language TTL was used, cf. [12]. This language is based on sorted first-order predicate logic, and allows making explicit references to time points and traces.…”

Section: Testing Strategy Performancementioning

confidence: 99%

The Distributed Weighing Problem: A Lesson in Cooperation Without Communication

Bosse

Hoogendoorn

Jonker

2005

Multiagent System Technologies

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Abstract. Cooperative problem solving without communication is an oftenstudied field within multi-agent research. Realistic problems investigated in this particular field are complex and difficult to model, and therefore not suitable for education. This paper presents the distributed weighing problem as a novel problem to be used for educational purposes within the domain of cooperation without communication. An example agent-based architecture is developed of which parts can be provided to students as a starting-point for practical exercises in cooperative problem solving without communication. Two example strategies are discussed and implemented using this example architecture. Moreover, it is shown how such strategies can be tested and formally validated against a number of desired properties. The educational benefits of the distributed weighing problem are presented as observed in a course for 6 groups of each 3 students.

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A temporal modelling environment for internally grounded beliefs, desires and intentions

Cited by 32 publications

References 16 publications

Formal modeling and analysis of cognitive agent behavior

Formal modeling and analysis of cognitive agent behavior

BDI-modelling of complex intracellular dynamics

The Distributed Weighing Problem: A Lesson in Cooperation Without Communication

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