The paradigm of bounded rationality considers the limited ability of individuals to make consistent and rational choices. Due to the scarcity of research on this phenomenon in information systems, we conducted an experimental study investigating decision-making regarding risk preferences and social preferences. Moreover, we explored the stability of these preferences under different conditions ...

A much discussed topic in the theory of choice is how a preference order among options can be derived from the assumption that the notion of ‘choice’ is primitive. Assuming a choice function that selects elements from each finite set of options, Arrow (1959) already showed how we can generate a weak ordering by putting constraints on the behavior of such a function such that it behaves as a uti...

According to Bayesian epistemology, the epistemically rational agent updates her beliefs by conditionalization: that is, her posterior subjective probability after taking account of evidence X, pnew, is to be set equal to her prior conditional probability pold(·/X). Bayesians can be challenged to provide a justification for their claim that conditionalization is recommended by rationality — whe...

Deliberation plays an important role in the design of rational agents embedded in the real-world. In particular, deliberation leads to the formation of intentions, i.e., plans of action that the agent is committed to achiev­ ing. In this paper, we present a branching­ time possible-worlds model for representing and reasoning about, beliefs, goals, inten­ tions, time, actions, probabilities, and...

This paper examines the implications of the brain sciences’ mechanistic model of human behavior for our understanding of crime. The rational crime model is replaced with a behavioral approach, which proposes a decision model comprising cognitive and emotional decision systems. According to the behavioral approach, a criminal is not irrational but rather ‘ecologically rational’, outfitted with e...

A problem that sometimes occurs in multiobjective optimization is the existence of a large set of Pareto-optimal solutions. Hence the decision making based on selecting a unique preferred solution becomes difficult. Considering models with rational B-efficiency relieves some of the burden from the decision maker by shrinking the solution set. This paper focuses on solving multiobjective optimiz...