科技英文作業 6

• 602410054 黃方世• 602410087 陳竹軒

Introduction

• Talking about video games.

• Training agents for what.

• Focus on training Non-player-character (NPC).

• Training agents offline or online.

Real-time NeuroEvolution of Augmenting Topologies (1)

• Based on NeuroEvolution of Augmenting Topologies (NEAT).

• Evolving neural networks for reinforcement learning tasks using genetic algorithm.

• Starting with simple networks; expand the search space only when beneficial.

Real-time NeuroEvolution of Augmenting Topologies (2)

•The worst individual is removed and replaced with a child of parents chosen from among the best.

Real-time NeuroEvolution of Augmenting Topologies (3)

•Choosing the parent species.

• . is the average fitness of species k; is the sum of all the average species’ fitness.

NeuroEvoluting Robotic Operatives (NERO)

• The exercises are increasingly difficult; the team can learning basic skills and gradually building on them.

Training Mode

• Robots have several types of sensors.

• The standard sensors include enemy radars, object rangefinders.

─Enemy radar divide 360 degrees around the robot into slices.

─Rangefinders project rays at several angles from the robot.

Playing NERO

• Training to run around walls to approach the enemy.

• Player incrementally add more walls until the robots can navigate an entire maze without any path-planning.