Local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. At a very high level, a local-ratio algorithm first decomposes ...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Combination of AI/OR methods is gaining a great deal of attention because many combinatorial problems especially in planning and scheduling areas can be solved by means of combined...
Propositional satisfiability solving, or SAT, is an important reasoning task arising in numerous applications, such as circuit design, formal verification, planning, scheduling or...
Entity matching is an important and difficult step for integrating web data. To reduce the typically high execution time for matching we investigate how we can perform entity matc...
Toralf Kirsten, Lars Kolb, Michael Hartung, Anika ...