Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
—This paper proposes a module-based vision for designing BDI-based multi-agent programming languages. The introduced concept of modules enables common programming techniques such...
Higher-order logic programming (HOLP) languages are particularly useful for various kinds of metaprogramming and theorem proving tasks because of the logical support for variable ...
We exhibit the rationale behind the design of Epigram, a dependently typed programming language and interactive program development system, using refinements of a well known progr...