Heuristic Problem-Solving

Search algorithms are typically made to optimize a well-defined criterion. Unfortunately, real-world problems are often hard to describe in a handful of variables. It is known from psychology that humans use a variety of heuristics, not only to limit the search space, but also leading to more appropriate solutions than well-defined "optimal" strategies. Herbert Simon has coined the term "satisficing" to describe solutions that are good enough for real problems and can be calculated with little effort.

Approach

We develop a heuristic search paradigm that combines different problem-specific (and possibly problem-unspecific) heuristics to solve a problem without an explicit optimization criterion. The first version, called Greedy Expert Search (GES), was based on a generalized search algorithm. In the next step, a new implementation as a blackboard architecture will be more general and include the option of a loose problem hierarchy.

TSP Dataset

Further Information

Posters

Hierarchical Knowledge for Heuristic Problem Solving - A Case Study on the Traveling Salesperson Problem
(First Annual Conference on Advances in Cognitive Systems, 2012)

Humanlike Problem Solving in the Context of the Traveling Salesperson Problem
(AAAI Fall Symposium on Advances in Cognitive Systems, 2011)

Publications

Hierarchical Knowledge for Heuristic Problem Solving --- A Case Study on the Traveling Salesperson Problem (Alexandra Kirsch), In First Annual Conference on Advances in Cognitive Systems, 2012. [pdf]

Humanlike Problem Solving in the Context of the Traveling Salesperson Problem (Alexandra Kirsch), In AAAI Fall Symposium on Advances in Cognitive Systems, 2011. [pdf]

Posters

Publications

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