… modeler from encoding knowledge in the agent. As we intend to show, designing an
environment-agnostic agent raises the crucial question of defining the agent’s drives. We employ …

… an agent to unseen environments. In this work, we propose Environment Agnostic Reinforce…
More recently, SVEA [13] design a stabilized Q-value estimation framework for dealing with …

… be significantly reduced if the agent can learn across diverse … In this work, we present a
flexible and environment-agnostic … that multi-environment training with one agent is possible in …

… , we propose an environment-agnostic learning method to … learned environment-agnostic
representations, the agent is … grounded multitask and environment-agnostic training regimes …

… We propose a design methodology that begins by indulging some hard-coded preconceptions
to get the spatial system running. In this first step, we setup and demonstrate the coupling …

… letting affordances emerge, by an artificial agent that initially ignores elements that compose
… Such an agent can be defined as environment-agnostic [6]. We base our work on a design …

… , we defined a design principle for artificial agents in which … This design principle is intended
to account for cognitive … We formalized the learning problem associated with this design …

… Hence we propose an environment-agnostic learning method … learned environment-agnostic
representations, the agent is … multitask and environment-agnostic training regimes and …

… agent can take a finite amount of reward-free interactions from a subset of these environments.
The agent … Can we design a provably efficient algorithm that achieves this ambitious goal …

… However, agent performance on the specific levels used in … introduce a new
environment-agnostic measure of behavioral … can improve the design of future multi-agent studies, …