Tibor Bosse

A Language and Environment for Analysis of Dynamics by SimulaTiOn

This article presents the language and software environment LEADSTO that has been developed to model and simulate dynamic processes in terms of both qualitative and quantitative concepts. The LEADSTO language is a declarative order-sorted temporal language, extended with quantitative notions like integer and real. Dynamic processes can be modelled in LEADSTO 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 data-files containing traces of simulation for further analysis, and constructs visual representations of traces. The approach proved its worth in a number of research projects in different domains.

SPECIFICATION AND VERIFICATION OF DYNAMICS IN AGENT MODELS

Within many domains, among which biological, cognitive, and social areas, multiple interacting processes occur among agents with dynamics that are hard to handle. This paper presents the predicate logical Temporal Trace Language (TTL) for the formal specification and analysis of dynamic properties of agents and multi-agent systems. This language supports the specification of both qualitative and quantitative aspects, and therefore subsumes specification languages based on differential equations and qualitative, logical approaches. A software environment has been developed for TTL, which supports editing TTL properties and enables the formal verification of properties against a set of traces. The TTL environment proved its value in a number of projects within different biological, cognitive and social domains.

Specification and Verification of Dynamics in Cognitive Agent Models

Within many domains, among which biological and cognitive areas, multiple interacting processes occur among agents with dynamics that are hard to handle. Current approaches to analyse the dynamics of such processes, often based on differential equations, are not always successful. As an alternative to differential equations, this paper presents the predicate logical temporal trace language (TTL) for the formal specification and analysis of dynamic properties. This language supports the specification of both qualitative and quantitative aspects, and therefore subsumes specification languages based on differential equations. A software environment has been developed for TTL, that supports editing TTL properties and enables the formal verification of properties against a set of traces. The TTL environment proved its value in a number of projects within different domains.

LEADSTO: a language and environment for analysis of dynamics by simulation

This paper presents the language and software environment LEADSTO that has been developed to model and simulate dynamic processes in terms of both qualitative and quantitative concepts. The LEADSTO language is a declarative order-sorted temporal language, extended with quantitative means. Dynamic processes 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 research projects in different domains.

Modelling collective decision making in groups and crowds: Integrating social contagion and interacting emotions, beliefs and intentions

Collective decision making involves on the one hand individual mental states such as beliefs, emotions and intentions, and on the other hand interaction with others with possibly different mental states. Achieving a satisfactory common group decision on which all agree requires that such mental states are adapted to each other by social interaction. Recent developments in social neuroscience have revealed neural mechanisms by which such mutual adaptation can be realised. These mechanisms not only enable intentions to converge to an emerging common decision, but at the same time enable to achieve shared underlying individual beliefs and emotions. This paper presents a computational model for such processes. As an application of the model, an agent-based analysis was made of patterns in crowd behaviour, in particular to simulate a real-life incident that took place on May 4, 2010 in Amsterdam. From available video material and witness reports, useful empirical data were extracted. Similar patterns were achieved in simulations, whereby some of the parameters of the model were tuned to the case addressed, and most parameters were assigned default values. The results show the inclusion of contagion of belief, emotion, and intention states of agents results in better reproduction of the incident than non-inclusion.

A Multi-agent Model for Emotion Contagion Spirals Integrated within a Supporting Ambient Agent Model

To avoid the occurrence of spirals of negative emotion in their teams, team leaders may benefit from intelligent agent systems that analyze the emotional dynamics of the team members. As a first step in developing such agents, this paper uses an agent-based approach to formalize and simulate emotion contagion spirals within groups. The computational multi-agent model is integrated within an intelligent ambient agent to monitor and predict group emotion levels over time and propose group support actions based on that.

Human vs. computer behavior in multi-issue negotiation

This paper presents two experiments that contribute to the comparison of human- versus computer behavior in the domain of multi-issue negotiation. The experiments are part of an ongoing endeavor of improving the quality of computer negotiators when negotiating against human negotiators. The validity of the experiments was tested in a case study of closed multi-issue negotiation involving the ABMP negotiation software agents. The results indeed reveal a number of strengths and weaknesses of the ABMP agents. For example, the fairness of deals in negotiations performed purely by ABMP agents is better than the fairness of deals in the comparable negotiations in which humans were involved. Furthermore, in mixed negotiations (i.e., involving human- and software agents) the humans outperform the software agent with respect to the individual performance. Based on the results of the experiments, several suggestions are made to improve the ABMP agents performance.

A computational model based on Gross' emotion regulation theory

Emotion regulation describes how a subject can use certain strategies to affect emotion response levels. Usually, models for emotion regulation assume mechanisms based on feedback loops that indicate how to change certain aspects of behavior or cognitive functioning in order to get a more satisfactory emotion response level. Adaptation of such feedback loops is usually left out of consideration. This paper introduces an adaptive computational model for emotion regulation by formalizing the model informally described by Gross (1998). The model has been constructed using a high-level modeling language, and integrates both quantitative aspects (such as levels of emotional response) and qualitative aspects (such as decisions to regulate ones emotion). This model includes mechanisms for adaptivity of the degree of flexibility of the emotion regulation process. Also, the effects of events like traumas or therapies on emotion regulation can be simulated. Based on this computational model, a number of simulation experiments have been performed and evaluated.

Agent-Based Modeling of Emotion Contagion in Groups

To avoid the development of negative emotion in their teams, team leaders may benefit from being aware of the emotional dynamics of the team members. To this end, the use of intelligent computer systems that analyze emotional processes within teams is a promising direction. As a first step toward the development of such systems, this paper uses an agent-based approach to formalize and simulate emotion contagion processes within groups, which may involve absorption or amplification of emotions of others. The obtained computational model is analyzed both by explorative simulation and by mathematical analysis. In addition, to illustrate the applicability of the model, it is shown how the model can be integrated within a computational ‘ambient agent model’ that monitors and predicts group emotion levels over time and proposes group support actions based on that. Based on this description, a discussion is provided of the main contribution of the model, as well as the next steps needed to incorporate it into real-world applications.

An Agent Model for a Human's Functional State and Performance

This paper presents an agent model of the dynamics of a humanpsilas functional state in relation to task performance and environment. It can be used in agent systems that support humans in demanding circumstances. Simulation experiments under different parameter settings pointed out that the model is able to produce realistic behaviour of different types of personalities. Moreover, by a mathematical analysis the equilibria of the model have been determined, and by automated checking a number of expected properties of the model have been confirmed.