Abstract

In my dissertation, I will propose Domain-Independent Dynamic Programming (DIDP), a novel model-based paradigm for combinatorial optimization (CO) based on dynamic programming (DP). In DIDP, a problem is first formulated as a declarative DP model and then solved by a general-purpose solver. The goal of my dissertation is to develop an algorithm-independent modeling formalism to define a DP model and general-purpose solvers for it and demonstrate that DIDP is promising for CO in practice. In particular, I will propose a modeling formalism based on a state transition system and heuristic search solvers for it.

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