Inter-temporal decisions involves assigning values to various payoffs occurring at different temporal distances. Past research has used different approaches to study these decisions made by humans and animals. For instance, considering that people discount future payoffs at a constant rate (e.g., exponential discounting) or at variable rate (e.g., hyperbolic discounting). In this research, we q...

Two solutions that occupy (almost) the same space in the objective space may have pre-images in the decision space that are essentially different. For a decision maker it can be interesting to know both pre-images in such cases. However, most Pareto optimization algorithms focus on diversity in the objective space only and thus will likely obtain only one solution. In this paper we propose a me...

Two solutions that occupy (almost) the same space in the objective space may have pre-images in the decision space that are essentially different. For a decision maker it can be interesting to know both pre-images in such cases. However, most Pareto optimization algorithms focus on diversity in the objective space only and thus will likely obtain only one solution. In this paper we propose a me...

The impossibility theorem of Dekel, Lipman and Rustichini [8] has been thought to demonstrate that standard state-space models cannot be used to represent unawareness. We first show that Dekel, Lipman and Rustichini do not establish this claim. We then distinguish three notions of awareness, and argue that although one of them may not be adequately modeled using standard state spaces, there is ...

We present a branch-and-bound algorithm for minimizing multiple convex quadratic objective functions over integer variables. Our method looks efficient points by fixing subsets of variables to values and using lower bounds in the form hyperplanes image space derived from continuous relaxations restricted functions. show that stops after finitely many fixings with detecting both full nondominate...