Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.

Abstract: As a new analogy paradigm of human learning process, reinforcement learning (RL) has become an emerging topic in computational intelligence (CI). The synergy between the RL and CI is an ...

Abstract: Due to the open nature of wireless communication, malicious electromagnetic jamming has long been a severe threat to the establishment and stability of communication links. To address this ...

A decade ago, DeepMind achieved a major AI breakthrough, enabling systems to learn retro video games like Space Invaders ...

The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 ...

If you have any confusion about the code or want to report a bug, please open an issue instead of emailing me directly, and unfortunately I do not have exercise answers for the book.

Specifically, machine learning algorithms can be trained on large datasets of patient information and mechanical ventilation settings. These algorithms can then predict patient responses to different ...

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...

OpenAI co-founder and former Director of AI at Tesla, who recently joined Anthropic—claims that X has become so toxic that he ...

This repository includes the code of algorithms used in the following paper: Liu, R., Piplani, R., & Toro, C. (2022). Deep reinforcement learning for dynamic ...