Reasoning in Highly Reactive Environments

TL;DR

This paper discusses the challenges and requirements for artificial agents to operate effectively in highly reactive environments characterized by sudden, unpredictable changes, emphasizing responsiveness, elasticity, and resilience.

Contribution

It defines key properties for agents in reactive environments and highlights ongoing research issues despite technological advances in AI.

Findings

Agents must be responsive, elastic, and resilient to operate effectively.

Current AI technologies enable reactive agents but many issues remain unsolved.

The paper identifies critical properties for agents in dynamic environments.

Abstract

The aim of my Ph.D. thesis concerns Reasoning in Highly Reactive Environments. As reasoning in highly reactive environments, we identify the setting in which a knowledge-based agent, with given goals, is deployed in an environment subject to repeated, sudden and possibly unknown changes. This is for instance the typical setting in which, e.g., artificial agents for video-games (the so called "bots"), cleaning robots, bomb clearing robots, and so on are deployed. In all these settings one can follow the classical approach in which the operations of the agent are distinguished in "sensing" the environment with proper interface devices, "thinking", and then behaving accordingly using proper actuators. In order to operate in an highly reactive environment, an artificial agent needs to be: 1. Responsive -> The agent must be able to react repeatedly and in a reasonable amount of time; 2. Elastic -> The agent must stay reactive also under varying workload; 3. Resilient -> The agent must stay responsive also in case of internal failure or failure of one of the programmed actions in the environment. Nowadays, thanks to new technologies in the field of Artificial Intelligence, it is already technically possible to create AI agents that are able to operate in reactive environments. Nevertheless, several issues stay unsolved, and are subject of ongoing research.