Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
This paper deals with the problem of controlling highly dynamic mechatronic systems. Such systems may work in several different operation modes, or even underlie continuous mode c...
Klaus Ecker, Andrei Tchernykh, Frank Drews, Silke ...
Agents often have to construct plans that obey resource limits for continuous resources whose consumption can only be characterized by probability distributions. While Markov Deci...
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
The CPS transformation dates back to the early 1970's, where it arose as a technique to represent the control flow of programs in -calculus based programming languages as -te...