Extração de preferências por meio de avaliações de comportamentos observados. / Preference elicitation using evaluation over observed behaviours.

AUTOR(ES)

Valdinei Freire da Silva

DATA DE PUBLICAÇÃO

2009

RESUMO

Recently, computer systems have been delegated to accomplish a variety of tasks, when the computer system can be more reliable or when the task is not suitable or not recommended for a human being. The use of preference elicitation in computational systems helps to improve such delegation, enabling lay people to program easily a computer system with their own preference. The preference of a person is elicited through his answers to specific questions, that the computer system formulates by itself. The person acts as an user of the computer system, whereas the computer system can be seen as an agent that acts in place of the person. The structure and context of the questions have been pointed as sources of variance regarding the users answers, and such variance can jeopardize the feasibility of preference elicitation. An attempt to avoid such variance is asking an user to choose between two behaviours that were observed by himself. Evaluating relatively observed behaviours turn questions more transparent and simpler for the user, decreasing the variance effect, but it might not be easier interpreting such evaluations. If divergences between agents and users perceptions occur, the agent may not be able to learn the users preference. Evaluations are generated regarding users perception, but all an agent can do is to relate such evaluation to his own perception. Another issue is that questions, which are exposed to the user through behaviours, are now constrained by the environment dynamics and a behaviour cannot be chosen arbitrarily, but the behaviour must be feasible and a policy must be executed in order to achieve a behaviour. Whereas the first issue influences the inference regarding users evaluation, the second problem influences how fast and accurate the learning process can be made. This thesis proposes the problem of Preference Elicitation under Evaluations over Observed Behaviours using the Markov Decision Process framework and theoretic properties in such framework are developed in order to turn such problem computationally feasible. The problem o different perceptions is analysed and constraint solutions are developed. The problem of demonstrating a behaviour is considered under the formulation of question based on stationary policies and non-stationary policies. Both type of questions was implemented and tested to solve the preference elicitation in a scenario with constraint conditions.

ASSUNTO(S)

autonomous agent inteligência artificial processos de markov artificial inteligence markovian decision processes behaviours machine learning bayesian inference robotics preference elicitation aprendizado computacional expected utility theory discovered preference hypothesis teoria da decisão

Documentos Relacionados

• Purinergic central pathways involved in the muscle blood flow regulation during alerting defense behaviours.
• Paisagem - lugares observados
• Sibling power: influence of older siblings' persuasive appeals on younger siblings' judgements about risk taking behaviours.
• Avaliacoes da infeccao de explantes de feijoeiro por Agrobacterium tumefaciens por meio de microscopia.
• Concepções de qualidade da educação básica forjadas por meio de avaliações em larga escala