Tag: AI
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Agents for Competitive Multi-Agent Autonomous Vehicle Racing: Learning-based vs Model-base
High-speed, multi-agent autonomous vehicle racing demands agents that can make split-second decisions while strategically interacting with unpredictable opponents. This thesis will develop a learning-based racing agent and a model-based one both capable of long-term reasoning, balancing raw speed with tactical maneuvers, and benchmark their performance under head-to-head competition. Requirements and tools Contacts: Michael Khayyat, Stefano