Zulfiqar Ali Memon

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.

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.

A RECURSIVE BDI AGENT MODEL FOR THEORY OF MIND AND ITS APPLICATIONS

This article discusses a formal belief, desire, intention (BDI)-based agent model for theory of mind (ToM). The model uses BDI concepts to describe the reasoning process of an agent that reasons about the reasoning process of another agent, which is also based on BDI concepts. We discuss three different application areas and illustrate how the model can be applied to each of them. We explore a case study for each of the application areas and apply our model to it. For each case study, a number of simulation experiments are described, and their results are discussed.

Designing human-awareness for ambient agents: A human mindreading perspective

Ambient Intelligence (AmI) [1] has the vision to make Information and Communication Technologies disappear into the environment thus creating an ergonomic space for the inhabitant, encompassing an active living environment around us. To bring this goal to realization, devices need to be built possessing knowledge about humans enabling these devices to show a more human-like understanding. For this, we need assistance of human-directed disciplines such as cognitive science, psychology and biomedical sciences that develop models for many different aspects of human functioning. By representing these models in a formal and computational format, and incorporating them in these devices, these devices can be made more sensitive and responsive to humans [3]. The integration of these models within AmI applications is becoming more widely known as human-aware ambient agent modelling. Theory of Mind (ToM), or mindreading, is an ability to attribute mental states such as, beliefs, intentions, desires, pretending, knowledge, emotion etc, to others and to understand that those states may be similar or different from ones own. The work presented in this thesis makes contributions in the area of modelling and simulation by analysing and designing ambient agent models integrating concepts of Theory of Mind, to make these models human-aware. To explore the applicability of the approach proposed in this thesis, it has been applied in different specializations addressing integrated approaches to, for example, emotion generation and reading, emotion contagion, believing, desiring, feeling, decision making, and attention [2].

An ambient agent model for group emotion support

This paper introduces an agent-based support model for group emotion, to be used by ambient systems to support teams in their emotion dynamics. Using model-based reasoning, an ambient agent analyzes the teams emotion level for present and future time points. In case the teams emotion level is found to become deficient, the ambient agent provides support to the team by proposing the team leader, for example, to give a pep talk to certain team members. The support model has been formally designed and within a dedicated software environment, simulation experiments have been performed.

A cognitive and neural model for adaptive emotion reading by mirroring preparation states and Hebbian learning

Two types of modelling approaches exist to reading an observed persons emotions: with or without making use of the observing persons own emotions. This paper focuses on an integrated approach that combines both types of approaches in an adaptive manner. The proposed models were inspired by recent advances in neurological context. Both a neural model and a more abstracted cognitive model are presented. In the first place emotion reading is modelled involving (preparatory) mirroring of body states of the observed person within the observing person. This involves a recursive body loop: a converging positive feedback loop based on reciprocal causation between preparations for body states and emotions felt. Here emotion reading involves the persons own body states and emotions in reading somebody elses emotions: first the same feeling is developed by mirroring, and after feeling the emotion, it is imputed to the other person. In the second place, as an extension an adaptive process is modelled based on Hebbian learning of a direct connection between a sensed stimulus concerning another agents body state (e.g., face expression) and an emotion imputation state. After this Hebbian learning process the emotion is imputed to the other agent before it is actually felt, or even without it is felt. Both the mirroring and Hebbian learning processes first have been modelled at a neural level, and next, in a more abstracted form at a cognitive level. By means of an interpretation mapping the paper shows the relation between the obtained cognitive model and the neurological model. In addition to specifications of both models and the interpretation mapping, simulation results are shown, and automated verification of relevant emerging properties is discussed.

An Adaptive Human-Aware Software Agent Supporting Attention-Demanding Tasks

This paper presents a human-aware software agent to support a human performing a task that demands substantial amounts of attention. The agent obtains human awareness in an adaptive manner by use of a dynamical model of human attention which is parameterised for specific characteristics of the human. The agent uses a built-in adaptation model to adapt on the fly the values of these parameters to the personal characteristics of the human. The software agent has been implemented in a component-based manner within the Adobe® Flex® environment.

On the reciprocal interaction between believing and feeling: an adaptive agent modelling perspective.

An agent’s beliefs usually depend on informational or cognitive factors such as observation or received communication or reasoning, but also affective factors may play a role. In this paper, by adopting neurological theories on the role of emotions and feelings, an agent model is introduced incorporating the interaction between cognitive and affective factors in believing. The model describes how the strength of a belief may not only depend on information obtained, but also on the emotional responses on the belief. For feeling emotions a recursive body loop between preparations for emotional responses and feelings is assumed. The model introduces a second feedback loop for the interaction between feeling and belief. The strength of a belief and of the feeling both result from the converging dynamic pattern modelled by the combination of the two loops. For some specific cases it is described, for example, how for certain personal characteristics an optimistic world view is generated in the agent’s beliefs, or, for other characteristics, a pessimistic world view. Moreover, the paper shows how such affective effects on beliefs can emerge and become stronger over time due to experiences obtained. It is shown how based on Hebbian learning a connection from feeling to belief can develop. As these connections affect the strenghts of future beliefs, in this way an effect of judgment ‘by experience built up in the past’ or ‘by gut feeling’ can be obtained. Some example simulation results and a mathematical analysis of the equilibria are presented.

An adaptive model for dynamics of desiring and feeling based on hebbian learning

Within cognitive models, desires are often considered as functional concepts that play a role in efficient focusing of behaviour. In practice a desire often goes hand in hand with having certain feelings. In this paper by adopting neurological theories a model is introduced incorporating both cognitive and affective aspects in the dynamics of desiring and feeling. Example simulations are presented, and both a mathematical and logical analysis is included.

Modelling the reciprocal interaction between believing and feeling from a neurological perspective

By adopting neurological theories on the role of emotions and feelings, an agent model is introduced incorporating the reciprocal interaction between believing and feeling. The model describes how the strength of a belief may not only depend on information obtained, but also on the emotional responses on the belief. For feeling emotions a recursive body loop is assumed. The model introduces a second feedback loop for the interaction between feeling and belief. The strength of a belief and of the feeling both result from the converging dynamic pattern modelled by the combination of the two loops. For some specific cases it is described, for example, how for certain personal characteristics an optimistic world view emerges, or, for other characteristics, a pessimistic world view.