14 papers
. We consider the problems of identifying LTL safety proper- ties and translating them to finite automata. We present an algorithm for constructing a finite automata recognising informative prefixes of LTL formulas based on [1]. The implementation also includes a procedure for de...
. Scalability issues may prevent users from verifying critical proper- ties of a complex hardware design. In this situation, we propose to synthesize a “safety shield” that is attached to the design to enforce the properties at run time. Shield synthesis can succeed where model c...
reward Environment Learning Agent Reinforcement learning algorithms discover policies that observation maximize reward, but do not necessarily guarantee safety dur- actions ing learning or execution phases. We introduce a new ap- proach to learn optimal policies while enforcing p...
. Temporal synthesis is the automated design of a system that interacts with an environment, using the declarative specification of the system’s behavior. A popular language for providing such a specification is Linear Temporal Logic, or LTL. LTL synthesis in the general case has...
A recent work [1] developed a shielding framework for single- Multi-agent reinforcement learning (MARL) has been increasingly agent reinforcement learning (RL), which synthesizes a shield to used in a wide range of safety-critical applications, which require enforce the correctne...
Three decades later, Parikh’s problem has been solved: This paper investigates first-order game logic and first-order Game logic is less expressive than the modal μ-calculus [2], modal μ-calculus, which extend their propositional modal because it embeds into the two-variable frag...
Reinforcement learning (RL) methods usually treat reward functions as black boxes. As such, these methods must extensively interact with the environment in order to discover rewards and optimal policies. In most RL applications, however, users have to program the reward function...
ones in such a way to satisfy the formula. LTL realizability Linear Temporal Logic (LTL) is the de-facto standard tempo- is 2EXPTIME-complete, on both infinite (Rosner 1992) and ral logic for system specification, whose foundational prop- finite (De Giacomo and Vardi 2015) traces...
: We present a novel theory of nonmonotonic temporal reasoning. It is related to approaches based on causation, the main di erence being that in our ap- proach causal relations take a context argument which indicates under what circumstances they should hold. Our theory can handl...
by (default or sampled) safe ones; action projection, e.g., (Cheng et al. 2019), where unsafe actions are replaced by We present Pure-Past Action Masking (PPAM), a lightweight approach to action masking for safe reinforcement learning. projecting them to the safe action space; an...
. Emerson-Lei conditions have recently attracted attention due to both their succinctness and their favorable closure properties. In the current work, we show how infinite-duration games with Emerson-Lei objectives can be analyzed in two different ways. First, we show that the Zi...