1 code implementation • 6 Mar 2023 • Wen-Chi Yang, Giuseppe Marra, Gavin Rens, Luc De Raedt
To this end, we introduce Probabilistic Logic Policy Gradient (PLPG).
no code implementations • 7 Nov 2022 • Gavin Rens, Wen-Chi Yang, Jean-François Raskin, Luc De Raedt
The task then consists of learning this unknown formula from states that are labeled as safe or unsafe by a domain expert.
no code implementations • 26 Sep 2020 • Gavin Rens, Jean-François Raskin, Raphaël Reynouad, Giuseppe Marra
In our formal setting, we consider a Markov decision process (MDP) that models the dynamics of the environment in which the agent evolves and a Mealy machine synchronized with this MDP to formalize the non-Markovian reward function.
no code implementations • 26 Aug 2020 • David Maoujoud, Gavin Rens
This paper studies multi-agent systems that involve networks of self-interested agents.
no code implementations • 25 Jan 2020 • Gavin Rens, Jean-François Raskin
There are situations in which an agent should receive rewards only after having accomplished a series of previous tasks.
no code implementations • 14 May 2018 • Gavin Rens, Abhaya Nayak, Thomas Meyer
We propose a new POMDP-based framework which is general enough for the specification of a variety of stochastic MAS domains involving the impact of agents on each other's reputations.
no code implementations • 2 May 2017 • Gavin Rens, Thomas Meyer
Imaging is a form of probabilistic belief change which could be employed for both revision and update.
no code implementations • 3 Jul 2016 • Gavin Rens, Deshendran Moodley
This article presents an agent architecture for controlling an autonomous agent in stochastic environments.
no code implementations • 7 Apr 2016 • Gavin Rens, Thomas Meyer, Giovanni Casini
In this work, an agent's beliefs are represented by a set of probabilistic formulae -- a belief base.
no code implementations • 7 Apr 2016 • Gavin Rens
I propose a framework for an agent to change its probabilistic beliefs when a new piece of propositional information $\alpha$ is observed.