Identifying Concepts Used by Human-Like Neural Network Chess Engines

As neural networks reach expert-level performance in many domains, there is growing interest in understanding the internal representations that guide their decisions. Models trained to mimic human decisions, rather than strive for optimal performance, offer a particularly interesting testbed for int