pkmn/ai

The home of competitive Pokémon artificial intelligence

ai's Issues

Inference

• information sets + perspectives
• valid inferences based on protocol
• reverse damage calculation
• leveraging usage stats
  • usage after already accounting for lead]
• possibly enhancements to statistics (joint probabilities, "correlation matrices")
• combining inferences with heuristics

Abstraction

• data bucketing
  • Kalose HP buckets
  • Athena RNG bucketing
• quantization (eg. storing usage stats as "q8" 1/256 probabilities at rest)
• logical/contextual input logs?

Time

• https://www.chessprogramming.org/Time_Management
• how the Pokémon Showdown timer works (in particular, on ladder)
• tracking |inactive| + clock skew
• pondering
• anytime algorithms/iterative deepening

Search

• tree bandit search + relation MCTS
• bandit algorithms
• (expecti)minimax
• alpha beta pruning
• search data structures
• parallelism

Evaluation

• https://www.chessprogramming.org/Evaluation
• analysis of existing HCE functions used by projects
• building blocks (hazards? # of remaining Pokémon, etc)
• evaluation through NN

Learning

• machine learning in Pokémon
• enhancements
• online learning (ie. during a game)
• NNUE in Pokémon
• embedding (poke2vec, pokemb)
• one shot learning on top of base model

Regret

• CFR in Pokemon
• modifications to CFR (MC-CFR, CFR+) etc