Specification and Verification of Dynamics in Agent Models

Bosse, Tibor; Jonker, Catholijn M.; Meij, Leander van der; Sharpanskykh, Alexei; Treur, Jan

doi:10.1142/s0218843009001987

Cited by 122 publications

(134 citation statements)

References 35 publications

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“…To formally compare the simulation results in Section 5 with the formalised transcripts presented in Section 3.2, the TTL Checker Tool [3] has been used. This piece of software enables the researcher to check whether certain expected (dynamic) properties, expressed as statements in the Temporal Trace Language (TTL) [3], hold for a given trace (defined as a time-indexed sequence of states).…”

Section: Formal Comparisonmentioning

confidence: 99%

“…This piece of software enables the researcher to check whether certain expected (dynamic) properties, expressed as statements in the Temporal Trace Language (TTL) [3], hold for a given trace (defined as a time-indexed sequence of states). Since the tool can take both simulated and empirical traces as input, it can be used to check (automatically) whether the generated simulation runs show similar patterns to the real world transcripts.…”

Section: Formal Comparisonmentioning

confidence: 99%

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Analysis of Beliefs of Survivors of the 7/7 London Bombings: Application of a Formal Model for Contagion of Mental States

Bosse

Chandra

Mitleton–Kelly

et al. 2011

Neural Information Processing

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Abstract. During emergency scenarios, the large number of possible influences inter se between cognitive and affective states of the individuals involved makes it difficult to analyse their (collective) behaviour. To study the behaviour of collectives of individuals during emergencies, this paper proposes a methodology based on formalisation of empirical transcripts and agent-based simulation, and applies this to a case study in the domain of the 7/7 London bombings in 2005. For this domain, first a number of survivor statements have been formalised. Next, an existing agent-based model has been applied to simulate the scenarios described in the statements. Via a formal comparison, the model was found capable of closely reproducing the real world scenarios.

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Section: Formal Comparisonmentioning

confidence: 99%

Section: Formal Comparisonmentioning

confidence: 99%

Analysis of Beliefs of Survivors of the 7/7 London Bombings: Application of a Formal Model for Contagion of Mental States

Bosse

Chandra

Mitleton–Kelly

et al. 2011

Neural Information Processing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Temporal perspectives on the dynamics of processes are addressed in a wide variety of literature, from different disciplines, including Cognitive Science , [3], [42], [56], and Artificial Intelligence and Computer Science [5], [12], [40], [13], [21], [31], [50], [59], [4]. Temporally local properties were used in Section 2 to describe the (physiological, cognitive, or behavioural) mechanisms of a process considered in a step-by-step manner.…”

Section: Lpp2 Activating Sensory Neurons For a Body Mapmentioning

confidence: 99%

A Three-Dimensional Abstraction Framework to Compare Multi-Agent System Models

Bosse

Hoogendoorn

Klein

et al. 2010

Computational Collective Intelligence. Technologies and Applications

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Models of agents or multiagent systems in a certain application area can be made at different levels of abstraction. The aim of this paper is to clarify different dimensions of abstraction. The three dimensions of considered are: the process abstraction dimension, the temporal dimension, and the agent cluster dimension. Thus a three-dimensional framework is obtained in which different types of multi-agent system models can be classified. For a number of multiagent system models in different application areas from the literature it is discussed how they fit in the framework.

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“…The properties were specified in the TTL language [4]. This predicate logical temporal language supports formal specification and analysis of dynamic properties, covering both qualitative and quantitative aspects.…”

Section: Verificationmentioning

confidence: 99%

“…For more details, see [4]. Automated tool support is also available that allows for verifying whether the properties hold in a set of simulation traces.…”

Section: Verificationmentioning

confidence: 99%

Computational Modeling and Analysis of Therapeutical Interventions for Depression

et al. 2010

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Abstract. Depressions impose a huge burden on both the patient suffering from a depression as well as society in general. In order to make interventions for a depressed patient during a therapy more personalized and effective, a supporting personal software agent can be useful. Such an agent should then have a good idea of the current state of the person. A computational model for human mood regulation and depression has been developed in previous work, but in order for the agent to give optimal support during an intervention, it should also have knowledge on the precise functioning of the intervention in relation with the mood regulation and depression. This paper therefore presents computational models for these interventions for different types of therapy. Simulation results are presented showing that the mood regulation and depression indeed follow the expected patterns when applying these therapies. The intervention models have been evaluated for a variety of patient types by simulation experiments and formal verification. IntroductionMajor depression is currently the fourth disorder worldwide in terms of disease burden, and is expected to be the disorder with the highest disease burden in highincome countries by the year 2030 (cf. [14]). Effective interventions for treating depressions are of utmost importance for both the patients suffering from a depression as well as for society in general. Supporting software agents can be very helpful in effectively treating a depression by providing personalized support for patients. Thereby, the agent can for example provide feedback on the current situation, give tips, and give certain tasks or assignments. In order for such a personal assistant agents to function effectively, it requires a detailed computational model on the relevant human states and their interrelationship regarding regulation of mood and depression. Such a model can also help to understand and analyze the basics behind a depression better. In [5] an example was shown of a computational model for mood regulation and depression based on literature on emotion and mood regulation. This model however does not explicitly address the functioning of interventions, such as activity scheduling [13] and cognitive restructuring [3]. Particularly for the domain of a personal assistant agent that supports patients during a major depression, knowledge

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Specification and Verification of Dynamics in Agent Models

Cited by 122 publications

References 35 publications

Analysis of Beliefs of Survivors of the 7/7 London Bombings: Application of a Formal Model for Contagion of Mental States

Analysis of Beliefs of Survivors of the 7/7 London Bombings: Application of a Formal Model for Contagion of Mental States

A Three-Dimensional Abstraction Framework to Compare Multi-Agent System Models

Computational Modeling and Analysis of Therapeutical Interventions for Depression

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