decision making with multiple imperfect decision makers - Institute of ...

Scope of the WorkshopPrescriptive Bayesian decision making supported by the efficient theoretically well-founded algorithms isknown to be a powerful tool. However, its application within multiple-participants’ settings needs anefficient support of imperfect participant (decision maker, agent), which is characterised by limited cognitive,acting and evaluative resources.The interacting and multiple-task-solving participants prevail in the natural (societal, biological) systems andbecome more and more important in the artificial (engineering) systems. Knowledge of conditions andmechanisms influencing the participant’s individual behaviour is a prerequisite to better understanding andrational improving of these systems. The diverse research communities permanently address these topicsfocusing either on theoretical aspects of the problem or (more often) on practical solution within a particularapplication. However, different terminology and methodologies used significantly impede furtherexploitation of any advances occurred. The workshop will bring the experts from different scientificcommunities to complement and generalise the knowledge gained relying on the multi-disciplinary wisdom.It extends the list of problems of the preceding NIPS workshop:How should we formalise rational decision making of a single imperfect decision maker? Does the answerchange for interacting imperfect decision makers? How can we create a feasible prescriptive theory forsystems of imperfect decision makers?The workshop especially welcomes contributions addressing the following questions:What can we learn from natural, engineered, and social systems? How emotions influence decision making?How to present complex prescriptive outcomes to the human? Do common algorithms really supportimperfect decision makers? What is the impact of imperfect designers of decision-making systems?The workshop aims to brainstorm on promising research directions, present relevant case studies andtheoretical results, and to encourage collaboration among researchers with complementary ideas andexpertise. The workshop will be based on invited talks, contributed talks and posters. Extensive moderatedand informal discussions ensure targeted exchange.List of Invited Talks• Automated Preferences ElicitationMiroslav Kárný, Tatiana V.Guy• Automated Explanations for MDP PoliciesOmar Zia Khan, Pascal Poupart, James P. Black• Modeling Humans as Reinforcement Learners: How to Predict Human Behavior in Multi˗ StageGamesRitchie Lee, David H. Wolpert, Scott Backhaus, Russell Bent, James Bono, Brendan Tracey• Random Belief LearningDavid Leslie• An Adversarial Risk Analysis Model for an Emotional Based Decision AgentJavier G. Rázuri, Pablo G. Esteban, David Rios Insua• Bayesian Combination of Multiple, Imperfect ClassifiersEdwin Simpson, Stephen Roberts, Ioannis Psorakis, Arfon Smith, Chris Lintott• Emergence of Reverse Hierarchies in Sensing and Planning by Optimizing Predictive InformationNaftali Tishby• Effect of Emotion on the Imperfectness of Decision MakingAlessandro E.P. Villa, Marina Fiori, Sarah Mesrobian, Alessandra Lintas,Vladyslav Shaposhnyk, Pascal Missonnier