An influence diagram represents a decision problem formalisation where the decision-maker is a rational one; i.e. he prefers the decision that maximises the utility function expected value. This formalism models the domain through a single homogeneous network and without considering the existence of specific sub-domains into the domain at hand. The main goal of this research project is to study the application of the multi-agent approach to the evaluation of influence diagrams, motivated by the intention of exploring the locality propriety in large domains. A domain that has locality can be looked by parts because it has specific and natural sub-domains. The decision-maker that reasons and decides based on the domain information can focus o...
Distributed Structure Abstract — For two decades, detection networks of various structures have been...
Open access article. This research received financial support from the internally funded DMU GCRF...
Influence diagrams have recently been used to analyse the safety and fairness properties of AI syste...
An influence diagram represents a decision problem formalisation where the decision-maker is a ratio...
In an earlier paper, a general approach to prescribing decision procedures for a command and control...
Multi-agent systems that use game-theoretic analysis for decision making traditionally take a normat...
This thesis is about how to represent and solve decision problems in Bayesian decision theory (e.g. ...
International audienceIn this paper, we focus on multi-criteria decision-making problems. We propose...
In descriptive decision and game theory, one specifies a model of a situation faced by agents and us...
This paper proposes a new decision making approch based on quantitative possibilistic influence diag...
AbstractThis paper is about how to represent and solve decision problems in Bayesian decision theory...
We consider the situation where two agents try to solve each their own task in a commonenvironment. ...
This thesis presents a new approach to local decision-making in multi-agent systems with varying amo...
An autonomous decision maker, such as an intelligent agent, must make decisions in the presence of u...
AbstractInspired by game theory representations, Bayesian networks, influence diagrams, structured M...
Distributed Structure Abstract — For two decades, detection networks of various structures have been...
Open access article. This research received financial support from the internally funded DMU GCRF...
Influence diagrams have recently been used to analyse the safety and fairness properties of AI syste...
An influence diagram represents a decision problem formalisation where the decision-maker is a ratio...
In an earlier paper, a general approach to prescribing decision procedures for a command and control...
Multi-agent systems that use game-theoretic analysis for decision making traditionally take a normat...
This thesis is about how to represent and solve decision problems in Bayesian decision theory (e.g. ...
International audienceIn this paper, we focus on multi-criteria decision-making problems. We propose...
In descriptive decision and game theory, one specifies a model of a situation faced by agents and us...
This paper proposes a new decision making approch based on quantitative possibilistic influence diag...
AbstractThis paper is about how to represent and solve decision problems in Bayesian decision theory...
We consider the situation where two agents try to solve each their own task in a commonenvironment. ...
This thesis presents a new approach to local decision-making in multi-agent systems with varying amo...
An autonomous decision maker, such as an intelligent agent, must make decisions in the presence of u...
AbstractInspired by game theory representations, Bayesian networks, influence diagrams, structured M...
Distributed Structure Abstract — For two decades, detection networks of various structures have been...
Open access article. This research received financial support from the internally funded DMU GCRF...
Influence diagrams have recently been used to analyse the safety and fairness properties of AI syste...