Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Previous type systems for mobility calculi (the original Mobile Ambients, its variants and descendants, e.g., Boxed Ambients and Safe Ambients, and other related systems) offer lit...
While software is becoming decomposed in more and more finegrained entities, the interactions amongst those become of major importance. While methodologies for building such compon...
In repeated games with incomplete information, rational agents must carefully weigh the tradeoffs of advantageously exploiting their information to achieve a short-term gain versu...
Social laws have proved to be a powerful and theoretically elegant framework for coordination in multi-agent systems. Most existing models of social laws assume that a designer is...