robopoker 0.1.1

use robopoker::*;

#[tokio::main(flavor = "multi_thread")]
async fn main() {
    // Boring stuff
    logs();
    // The k-means earth mover's distance hand-clustering algorithm.
    clustering::learner::Hierarchical::upload();
    // Monet Carlo counter-factual regret minimization. External sampling, alternating regret updates, linear weighting schedules.
    mccfr::trainer::Blueprint::train(100_000);
    // After 100s of CPU-days of training in the arena, the CPU is ready to see you.
    play::game::Game::play();
}

//  + 2019. Superhuman AI for multiplayer poker. (https://science.sciencemag.org/content/early/2019/07/10/science.aay2400) Science, July 11th.
//    2019. Regret Circuits: Composability of Regret Minimizers. In Proceedings of the International Conference on Machine Learning (ICML), 2019. arXiv version. (https://arxiv.org/abs/1811.02540)
//    2019. Stable-Predictive Optimistic Counterfactual Regret Minimization. In ICML. arXiv version. (https://arxiv.org/pdf/1902.04982.pdf)
//    2019. Deep Counterfactual Regret Minimization In ICML. Early version (https://arxiv.org/pdf/1811.00164.pdf) in NeurIPS-18 Deep RL Workshop, 2018.
//  + 2019. Solving Imperfect-Information Games via Discounted Regret Minimization (https://arxiv.org/pdf/1809.04040.pdf). In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
//    2019. Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games (http://www.cs.cmu.edu/~gfarina/2018/laminar-regret-aaai19/). In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
//    2019. Quasi-Perfect Stackelberg Equilibrium (http://www.cs.cmu.edu/~gfarina/2018/qp-stackelberg-aaai19/). In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
//    2019. Stable-Predictive Optimistic Counterfactual Regret Minimization (https://arxiv.org/pdf/1902.04982.pdf). arXiv.
//    2018. Faster algorithms for extensive-form game solving via improved smoothing functions. (https://rdcu.be/8EyP) Mathematical Programming, Series A. Abstract published in EC-17.
//  + 2018. Depth-Limited Solving for Imperfect-Information Games. (https://arxiv.org/pdf/1805.08195.pdf) In Proc. Neural Information Processing Systems (NeurIPS).
//    2018. A Unified Framework for Extensive-Form Game Abstraction with Bounds. In NIPS. Early version (http://www.cs.cmu.edu/~ckroer/papers/unified_abstraction_framework_ai_cubed.pdf) in IJCAI-18 AI^3 workshop.
//    2018. Practical Exact Algorithm for Trembling-Hand Equilibrium Refinements in Games. (http://www.cs.cmu.edu/~gfarina/2017/trembling-lp-refinements-nips18/) In NeurIPS.
//    2018. Solving Large Sequential Games with the Excessive Gap Technique. (https://arxiv.org/abs/1810.03063) In NeurIPS. Also Spotlight presentation.
//    2018. Ex Ante Coordination and Collusion in Zero-Sum Multi-Player Extensive-Form Games. (http://www.cs.cmu.edu/~gfarina/2018/collusion-3players-nips18/) In NeurIPS.
//    2018. Trembling-Hand Perfection in Extensive-Form Games with Commitment. (http://www.cs.cmu.edu/~ckroer/papers/stackelberg_perfection_ijcai18.pdf) In IJCAI.
//    2018. Robust Stackelberg Equilibria in Extensive-Form Games and Extension to Limited Lookahead. (http://www.cs.cmu.edu/~ckroer/papers/robust.aaai18.pdf) In Proc. AAAI Conference on AI (AAAI).
//  + 2017. Safe and Nested Subgame Solving for Imperfect-Information Games. (https://www.cs.cmu.edu/~noamb/papers/17-NIPS-Safe.pdf) In NIPS. * *Best Paper Award, out of 3,240 submissions.
//    2017. Regret Minimization in Behaviorally-Constrained Zero-Sum Games. (http://www.cs.cmu.edu/~sandholm/behavioral.icml17.pdf) In Proc. International Conference on Machine Learning (ICML).
//  + 2017. Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning. (http://www.cs.cmu.edu/~sandholm/reducedSpace.icml17.pdf) In ICML.
//    2017. Smoothing Method for Approximate Extensive-Form Perfect Equilibrium. (http://www.cs.cmu.edu/~sandholm/smoothingEFPE.ijcai17.pdf) In IJCAI. ArXiv version. (http://arxiv.org/abs/1705.09326)
//    2017. Dynamic Thresholding and Pruning for Regret Minimization. (http://www.cs.cmu.edu/~sandholm/dynamicThresholding.aaai17.pdf) In AAAI.
//    2016. Imperfect-Recall Abstractions with Bounds in Games. (http://www.cs.cmu.edu/~sandholm/imperfect-recall-abstraction-with-bounds.ec16.pdf) In Proc. ACM Conference on Economics and Computation (EC).
//    2016. Strategy-Based Warm Starting for Regret Minimization in Games. In AAAI. Extended version with appendix. (http://www.cs.cmu.edu/~sandholm/warmStart.aaai16.withAppendixAndTypoFix.pdf)
//  + 2015. Regret-Based Pruning in Extensive-Form Games. (http://www.cs.cmu.edu/~sandholm/cs15-892F15) In NIPS. Extended version. (http://www.cs.cmu.edu/~sandholm/regret-basedPruning.nips15.withAppendix.pdf)
//    2015. Simultaneous Abstraction and Equilibrium Finding in Games. (http://www.cs.cmu.edu/~sandholm/simultaneous.ijcai15.pdf) In IJCAI.
//    2015. Limited Lookahead in Imperfect-Information Games. (http://www.cs.cmu.edu/~sandholm/limited-look-ahead.ijcai15.pdf) IJCAI.
//    2015. Faster First-Order Methods for Extensive-Form Game Solving. (http://www.cs.cmu.edu/~sandholm/faster.ec15.pdf) In EC.
//    2015. Hierarchical Abstraction, Distributed Equilibrium Computation, and Post-Processing, with Application to a Champion No-Limit Texas Hold’em Agent. (http://www.cs.cmu.edu/~sandholm/hierarchical.aamas15.pdf) In Proc. Internat. 20Conference on Autonomous Agents and Multiagent Systems (AAMAS).
//    2015. Discretization of Continuous Action Spaces in Extensive-Form Games. (http://www.cs.cmu.edu/~sandholm/discretization.aamas15.fromACM.pdf) In AAMAS.
//    2015. Endgame Solving in Large Imperfect-Information Games. (http://www.cs.cmu.edu/~sandholm/endgame.aamas15.fromACM.pdf) In AAMAS.
//    2014. Extensive-Form Game Abstraction With Bounds. (http://www.cs.cmu.edu/~sandholm/extensiveGameAbstraction.ec14.pdf) In EC.
//    2014. Regret Transfer and Parameter Optimization. (http://www.cs.cmu.edu/~sandholm/regret_transfer.aaai14.pdf) In AAAI.
//  + 2014. Potential-Aware Imperfect-Recall Abstraction with Earth Mover’s Distance in Imperfect-Information Games. (http://www.cs.cmu.edu/~sandholm/potential-aware_imperfect-recall.aaai14.pdf) In AAAI.
//  + 2013. Action Translation in Extensive-Form Games with Large Action Spaces: Axioms, Paradoxes, and the Pseudo-Harmonic Mapping. (http://www.cs.cmu.edu/~sandholm/reverse%20mapping.ijcai13.pdf) In IJCAI.
//  + 2013. A Fast and Optimal Hand Isomorphism Algorithm. In the Second Computer Poker and Imperfect Information Symposium at AAAI. (https://www.cs.cmu.edu/~waugh/publications/isomorphism13.pdf)
//    2012. Lossy Stochastic Game Abstraction with Bounds. (http://www.cs.cmu.edu/~sandholm/lossyStochasticGameAbstractionWBounds.ec12.pdf) In EC.
//    2012. First-Order Algorithm with O(ln(1/epsilon)) Convergence for epsilon-Equilibrium in Two-Person Zero-Sum Games. (http://www.cs.cmu.edu/~sandholm/restart.MathProg12.pdf) Mathematical Programming 133(1-2), 279-298. Subsumes our AAAI-08 20paper.
//    2012. Strategy Purification and Thresholding: Effective Non-Equilibrium Approaches for Playing Large Games. (http://www.cs.cmu.edu/~sandholm/StrategyPurification_AAMAS2012_camera_ready_2.pdf) In AAMAS.
//    2012. Tartanian5: A Heads-Up No-Limit Texas Hold'em Poker-Playing Program. (http://www.cs.cmu.edu/~sandholm/Tartanian_ACPC12_CR.pdf) Computer Poker Symposium at AAAI.
//    2010. Smoothing techniques for computing Nash equilibria of sequential games. (http://www.cs.cmu.edu/~sandholm/proxtreeplex.MathOfOR.pdf) Mathematics of Operations Research 35(2), 494-512.
//    2010. Computing Equilibria by Incorporating Qualitative Models (http://www.cs.cmu.edu/~sandholm/qualitative.aamas10.pdf). In AAMAS. Extended version (http://www.cs.cmu.edu/~sandholm/qualitative.TR10.pdf): CMU technical report 20CMU-CS-10-105.
//    2010. Speeding Up Gradient-Based Algorithms for Sequential Games (Extended Abstract) (http://www.cs.cmu.edu/~sandholm/speedup.aamas10.pdf). In AAMAS.
//    2009. Computing Equilibria in Multiplayer Stochastic Games of Imperfect Information (http://www.cs.cmu.edu/~sandholm/stochgames.ijcai09.pdf). In IJCAI.

fn logs() {
    use std::io::Write;
    use tokio::time::Instant;
    let start = Instant::now();
    env_logger::Builder::new()
        .filter(None, log::LevelFilter::Info)
        .format(move |buffer, record| {
            let elapsed = start.elapsed();
            writeln!(
                buffer,
                "{:02}:{:02}:{:02} - {}",
                (elapsed.as_secs() / 3600),
                (elapsed.as_secs() % 3600) / 60,
                (elapsed.as_secs() % 60),
                record.args()
            )
        })
        .init();
}