Abstract. This paper presents the language and software environment LEADSTO that has been developed to model and simulate the dynamics of Multi-Agent Systems (MAS) in terms of both qualitative and quantitative concepts. The LEADSTO language is a declarative order-sorted temporal language, extended with quantitative means. Dynamics of MAS can be modelled by specifying the direct temporal dependencies between state properties in successive states. Based on the LEADSTO language, a software environment was developed that performs simulations of LEADSTO specifications, generates simulation traces for further analysis, and constructs visual representations of traces. The approach proved its value in a number of projects within different domains of MAS research. 1

This paper contributes an analysis and formalisation of Damasio’s theory on core consciousness. Three important concepts in this theory are ‘emotion’, ‘feeling’, and ‘feeling a feeling ’ (or core consciousness). In particular, a simulation model is described of the dynamics of basic mechanisms leading via emotion and feeling to core consciousness, and dynamic properties are formally specified that hold for these dynamics at a more global level. These properties have been automatically checked for the simulation model. Moreover, a formal analysis is made of relevant notions of representation used by Damasio. As part of this analysis, specifications of representation relations have been verified and confirmed against the simulation model. 1

Abstract. Agent-based simulation methods are a relatively new way to address complex systems. Usually the idea is that the agents used are rather simple, and the complexity and adaptivity of such a system are modelled by the interaction between these agents. However, another way to exploit agent-based simulation methods is by use of agents that themselves also have certain forms of learning or adaptation. In order to simulate adaptive agents with abilities matching those of their real-world biological or societal counterparts, a natural approach is to incorporate certain adaptation mechanisms such as classical conditioning into agent models. Existing models for adaptation mechanisms are usually based on quantitative, numerical methods, and more in particular, differential equations. Since agent-based simulation is usually based on qualitative, logical languages, these quantitative models are often not directly appropriate as an input in the context of agent-based simulation. To deal with this problem, this paper puts forward an integrative approach to simulate and analyse the dynamics of a conditioning process of an adaptive agent, integrating quantitative, numerical and qualitative, logical aspects within one expressive temporal specification language. To obtain a simulation model, an executable sublanguage of this language is used to specify the agent’s adaptation

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.

From an external perspective, cognitive agent behaviour can be described by specifying (temporal) correlations of a certain complexity between stimuli (input states) and (re)actions (output states) of the agent. From an internal perspective the agent’s dynamics can be characterized by direct (causal) temporal relations between internal cognitive states of the agent. Internal dynamics and externally observable behaviour of an agent have reciprocal relations with each other. This paper contributes an approach that allows automatic generation of a behavioural specification of an agent from a cognitive process model. Furthermore, by this automated transformation, internal cognitive state properties of an agent can be related by a representation relation to externally observable behavioural patterns. 1.

Abstract. To enable the development of automated support for the dynamics of design processes, a challenge is to model and analyse such dynamics in a formal manner. This paper contributes a declarative, logical approach for specification of dynamic properties of design processes, supported by a formal temporal language which has a high expressivity. This language can be used to specify dynamic properties at the level of a design process as a whole, or of parts thereof. At the most detailed level, in an executable sublanguage also simulation models are specified in a declarative, logical manner, which allows to use these specifications in logical analysis as well. The approach is illustrated by an example component-based agent-system design process. 1.

Abstract. Recognizing that trust states are mental states, this paper presents a formal analysis of the dynamics of trust in terms of the functional roles and representation relations for trust states. This formal analysis is done both in a logical framework and in a mathematical framework based on integral and differential equations. Furthermore, the paper presents formal specifications of a number of relevant dynamic properties of trust. The specifications provided were used to perform automated formal analysis of empirical and simulated data from two case studies, one involving two experiments with humans, and one involving simulation experiments in the context of an economic game.

Many aspects affect the way humans perform tasks: not only the content of a task, but also somebody’s personality or his or her current exhaustion. Under varying conditions the quality of the performance is known to vary, for example, due to biases that occur. This paper introduces a cognitive model addressing these aspects. It has been formally specified, tested in simulations for various scenarios, and formally analysed.

Reduction relations, automated mapping of specifications, cognitive science Knowledge can be specified at different levels of conceptualisation or abstraction. In this paper, lessons learned on the philosophical foundations of cognitive science are discussed, with a focus on how the relationships of cognitive theories with specific underlying (physical/biological) makeups can be dealt with. It is discussed how these results can be applied to relate different types of knowledge specifications. More specifically, it is shown how different knowledge specifications can be related by means of reduction relations, similar to how specifications of cognitive theories can be related to specifications within physical or biological contexts. By the example of a specific reduction approach, it is shown how the process of reduction can be automated, including mapping of specifications of different types and checking the fulfilment of reduction conditions. 1

Many aspects affect the way humans perform tasks, among others somebody’s personality and current exhaustion level. Under varying conditions the quality of the performance is known to vary as well, for example, due to biases that occur. This paper introduces a cognitive control model addressing these aspects. It has been formally specified, tested in simulations for various scenarios, and formally analyzed.