3 ms·
To add to Galanwe's point: Wikipedia says (about AlphaGo): "AlphaGo's playing style strongly favours greater probability of winning by fewer points over lesse
by z5h 5y ago
To add to Galanwe's point:
Wikipedia says (about AlphaGo):
"AlphaGo's playing style strongly favours greater probability of winning by fewer points over lesser probability of winning by more points. Its strategy of maximizing its probability of winning is distinct from what human players tend to do which is to maximize territorial gains, and explains some of its odd-looking moves."
In other words optimizing the likelihood of winning looks strange to experts who use other heuristics to assess positions.
- AussieWog93 5y agoI'm not a chess player, but I was into competitive Pokémon for a time. Any decent player will prioritise win probability over loss minimisation, even to the point of sacrificing multiple Pokémon to get a single turn of setup with your main sweeper. While it seems confusing to newbies, experienced players know exactly why they're making the choices that they are.
- Agentlien 5y agoThe same is true of Magic: The Gathering where an oft repeated lesson is "life is a resource". Meaning you shouldn't be afraid to spend it to win. My guess would be that for chess it's more difficult to gauge the difference in real time.
- z5h 5y agoRight. I’m saying expert human players of deep and complex games still have a heuristic tied to human concepts: piece count, piece value, safety, mobility, etc. So a professional considering a line of play might be turned off that line if one of those measures would suffer. There are some amazing games of Alpha Zero playing Stockfish (the other best chess program) where it seems Alpha Zero just doesn’t give a fuck. It’s just sacrificing it’s own pieces and not clear (to a human… or Stockfish) what the plan is. Later it achieves a zugzwang against Stockfish, which is the most humiliating thing it could do (if either program had emotions).
- thoughtstheseus 5y agoEspecially given the rise of speed chess over the last few years. Focus on solid heuristics and speed, not finding strictly optimal moves.