Poker Is Harder for AI to Master Than Chess. AI has Now Learned to Bluff and Beat Humans.

The list of recent defeats where humans were overmatched by machines are well-known: chess champion Garry Kasparov losing against IBM's Deep Blue, Jeopardy wiz Ken Jennings being soundly defeated by IBM's Watson, and Go champion Lee Sodol losing to Google's AlphaGo. We may also be able to add poker to the list of AI superiority. A recent twenty-day competition between poker champions (heads-up no-limit Texas hold'em, 120,000 total hands) and Libratus, an AI program created by Carnegie Mellow University professors Tuomas Sandholm and Noam Brown, had the AI coming out on top. This is particularly surprising because unlike games like chess and Go, where the information is upfront and know ("Perfect Information Games"), poker involves a great deal of hidden information ("Imperfect Information Games") and the seemingly-human characteristic of bluffing. It turns out that AI can learn the art of bluffing.