@article { marques13, abstract = {Creating autonomous virtual agents capable of exhibiting human-like behaviour under uncertainty is becoming increas- ingly relevant, for instance in multi-agent based simulations (MABS), used to validate social theories, and also as intelli- gent characters in virtual training environments (VTEs). The agents in these systems should not act optimally; instead, they should display intrinsic human limitations and make judge- ment errors. We propose a Belief-Desire-Intention (BDI) based model which allows for the emergence of uncertainty re- lated biases during the agent’s deliberation process. To achieve it, a probability of success is calculated from the agent’s beliefs and attributed to each available intention . These probabilities are then combined with the intention’s utility using Prospect Theory, a widely validated descriptive model of human deci- sion. We also distinguish risk from ambiguity, and allow for individual variability in attitudes towards these two types of uncertainty through the specification of indices. In a travelling scenario, we demonstrate how distinct, more realistic agent be- haviours can be obtained by applying the proposed model.}, journal = {Cogsci 2013- The annual Meeting of the Cognitive Science Society}, keywords = {Intelligent Virtual Agents;Affective Computing;}, title = {Towards agents with human-like decisions under uncertainty}, year = {2013}, author = {Nuno Marques and Francisco S. Melo and Samuel Mascarenhas and João Dias and Rui Prada and Ana Paiva} }

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