MICo: Improved representations via sampling-based state similarity for Markov decision processes
We present a new behavioural distance over the state space of a Markov decision process,
and demonstrate the use of this distance as an effective means of shaping the learnt …
and demonstrate the use of this distance as an effective means of shaping the learnt …
[图书][B] Distributional reinforcement learning
The first comprehensive guide to distributional reinforcement learning, providing a new
mathematical formalism for thinking about decisions from a probabilistic perspective …
mathematical formalism for thinking about decisions from a probabilistic perspective …
Learning model checking and the kernel trick for signal temporal logic on stochastic processes
We introduce a similarity function on formulae of signal temporal logic (STL). It comes in the
form of a kernel function, well known in machine learning as a conceptually and …
form of a kernel function, well known in machine learning as a conceptually and …
stl2vec: Semantic and Interpretable Vector Representation of Temporal Logic
Integrating symbolic knowledge and data-driven learning algorithms is a longstanding
challenge in Artificial Intelligence. Despite the recognized importance of this task, a notable …
challenge in Artificial Intelligence. Despite the recognized importance of this task, a notable …