Contrastive Reinforcement Learning of Symbolic Reasoning Domains

Understand

Abstract symbolic reasoning, as required in domains such as mathematics and logic, is a key component of human intelligence.

• Solvers for these domains have important applications, especially to computer-assisted education.
• But learning to solve symbolic problems is challenging for machine learning algorithms.
• Existing models either learn from human solutions or use hand-engineered features, making them expensive to apply in new domains.