Decisions Based upon Multiple Values: The BVG Agent Architecture

Antunes, Luís; Coelho, Hélder

doi:10.1007/3-540-48159-1_21

Cited by 8 publications

(21 citation statements)

References 2 publications

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“…2), and does not include emotions. This new sketch expands on the one presented in [2], where the primary focus was laid on choice. Now, we turn our attention towards control.…”

Section: The Bvg Architecturementioning

confidence: 91%

“…In a similar line of reasoning, we have addressed the issue of choice, as one of the central components in the agent's decision machinery [1,2,3]. We have proposed the use of multiple values to assess a decision situation.…”

Section: Agents With Valuesmentioning

confidence: 99%

“…The multiple values framework we defend can encompass Simon's aspiration levels, but it is more general, allowing for further flexibility, as is shown in [3]. In [2], we present an example of the use of values in a decision problem: imagine someone wants to solve some trouble with his computer. There are several ways of achieving this goal.…”

Section: Agents With Valuesmentioning

confidence: 99%

“…This is done by feeding back evaluative information about the results of the decision taken by the agent. In [2] this assessment of (the results of) the decision was done by using some measure of goodness (an abstract higher value). We also suggested other alternatives, such as the agent's own values, or the designer's values (which amounts to looking for emergent features in the agent's behaviour, that is, agents decide by using some system of values, but the designer is interested in what happens to another set of values, to which the agents do not have access).…”

Section: Agents With Valuesmentioning

confidence: 99%

“…One way of achieving this without over-determining the behaviour of the agent, and even so reducing the deliberation time would be to have several partial ordered sets of actions, and computing the final order only when the moment arrives. The BVG architecture introduced in [2] paid special attention to choice. Now it is time to get the whole of the agent's decision machinery in context, and consider a broader picture.…”

Section: The Bvg Architecturementioning

confidence: 99%

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Redesigning the Agents’ Decision Machinery

Antunes

Coelho

2000

Affective Interactions

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Abstract. In a multi-agent system, agents must decide what to do and by what order. Autonomy is a key notion in such a system, since it is mainly the autonomy of the agents that makes the environment unpredictable and complex. From a user standpoint, autonomy is equally important as an ingredient that has to be used with parsimony: too much leads to agents fulfilling their own goals instead of those of the user, too little renders agents that are too dependent upon user commands and choices for their execution. Autonomy has a role in deciding which are the new goals of the agent, and it has another in choosing which of the agent's goals are going to be addressed next. We have proposed the BVG (Beliefs, Values, Goals) architecture with the idea of making decisions using multiple evaluations of a situation, taking the notion of value as central in the motivational mechanisms in the agent's mind. The agent will consider the several evaluations and decide in accordance with its goals in a rational fashion. In this paper we extend this architecture in three different directions: we consider the source of agent's goals, we enhance the decisional mechanisms to consider a wider range of situations, and we introduce emotion as a meta-level control mechanism of the decision processes.

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“…2), and does not include emotions. This new sketch expands on the one presented in [2], where the primary focus was laid on choice. Now, we turn our attention towards control.…”

Section: The Bvg Architecturementioning

confidence: 91%

Section: Agents With Valuesmentioning

confidence: 99%

Section: Agents With Valuesmentioning

confidence: 99%

Section: Agents With Valuesmentioning

confidence: 99%

Section: The Bvg Architecturementioning

confidence: 99%

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Redesigning the Agents’ Decision Machinery

Antunes

Coelho

2000

Affective Interactions

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Analysing Partner Selection Through Exchange Values

Rodrigues

Lück

2006

Lecture Notes in Computer Science

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Dynamic and resource-constrained environments raise interesting issues for partnership formation and multi-agent systems. In a scenario in which agents interact with each other to exchange services, if computational resources are limited, agents cannot always accept a request, and may take time to find available partners to delegate their needed services. Several approaches are available to solve this problem, which we explore through an experimental evaluation in this paper. In particular, we provide a computational implementation of Piaget's exchange-values theory, and compare its performance against alternatives.

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Regulating Social Exchanges Between Personality-Based Non-transparent Agents

Dimuro

Costa

Gonçalves

et al. 2006

Lecture Notes in Computer Science

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Abstract. This paper extends the scope of the model of regulation of social exchanges based on the concept of a supervisor of social equilibrium. We allow the supervisor to interact with personality-based agents that control the supervisor access to their internal states, behaving either as transparent agents (agents that allow full external access to their internal states) or as non-transparent agents (agents that restrict such external access). The agents may have different personality traits, which induce different attitudes towards both the regulation mechanism and the possible profits of social exchanges. Also, these personality traits influence the agents' evaluation of their current status. To be able to reason about the social exchanges among personality-based non-transparent agents, the equilibrium supervisor models the system as a Hidden Markov Model.

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Decisions Based upon Multiple Values: The BVG Agent Architecture

Cited by 8 publications

References 2 publications

Redesigning the Agents’ Decision Machinery

Redesigning the Agents’ Decision Machinery

Analysing Partner Selection Through Exchange Values

Regulating Social Exchanges Between Personality-Based Non-transparent Agents

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