Probabilistic design of optimal sequential decision-making algorithms in learning and control

Data mining for decision making in engineering optimal design

Often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. Instead it is obtained by some numerical analysis such as FE structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. Yet, the numerical analyses are considerably time consuming to obtain the final value of objective functi...

Learning and Sequential Decision Making

Structure Learning in Human Sequential Decision-Making

Studies of sequential decision-making in humans frequently find suboptimal performance relative to an ideal actor that has perfect knowledge of the model of how rewards and events are generated in the environment. Rather than being suboptimal, we argue that the learning problem humans face is more complex, in that it also involves learning the structure of reward generation in the environment. ...

Scalable Algorithms for Multiagent Sequential Decision Making

Introduction In artificial intelligence, decision theory deals with computing a sequence of actions (policy) that an autonomous agent must take in order to optimize its rewards (obtain its goals in the most efficient manner). In many real world situation , an autonomous agent must deal with various sources of uncertainty while computing its optimal policy. In single agent settings, such decisio...

data mining for decision making in engineering optimal design

often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. instead it is obtained by some numerical analysis such as fe structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. yet, the numerical analyses are considerably time consuming to obtain the final value of objective functi...