Learning in Games ChiJen Lu Academia Sinica Outline
- Slides: 32
Learning in Games Chi-Jen Lu Academia Sinica
Outline What machine learning can do for game theory What game theory can do for machine learning
TWO-PLAYER ZERO-SUM GAMES
Zero-sumgames player 2 player 1 0 -1 1 0 1 -1 1 0 -1 -1 0 utility (reward) of player 1 utility (reward) of player 2
Zero-sumgames < in many games
Zero-sumgames distributions
ONLINE LEARNING
Online learning / decision Making decisions/predictions repeatedly and then paying the prices I wish I had…
Many examples Predicting weather, trading stocks, commuting to work, … Network routing Scheduling Resource allocation Online advertising …
Problem formulation distribution over K
Goal: minimize regret Regret: total reward of best fixed strategy total reward of online algorithm I wish I had…
No-regretalgorithms no regret
Applications in other areas algorithms: approximation algorithms complexity: hardcore set for derandomization optimization: LP duality biology: evolution game theory: minimax theorem 13
Zero-sumgames distributions huge? oneshot game
INFLUENCE MAXIMIZATION GAMES
Opinion formation in social net A population of n individuals, each with some internal opinion from [-1, 1] vs. Each tries to express an opinion close to neighbors’ opinions and her internal one 16
Opinion formation in social net Zero-sum game between and player/party: ◦ goal: makes n shades of grey darker lighter ◦ actions: controls the opinions of k individuals Find minimax strategy? 17
Opinion formation in social net Zero-sum game between and player/party: ◦ goal: makes n shades of grey darker lighter ◦ actions: controls the opinions of k individuals Find minimax strategy? Solution: no-regret algorithm for online combinatorial optimization. follow the perturbed leader 18
MARKOV GAMES
Games with states board configurations policy: states actions (randomized) Minimax theorem: policy
Games with states board configurations policy huge?
Games with states Solution: no-regret algorithm for twoplayer Markov decision process Time, space poly(#(states), #(actions)) still huge for many games
Outline What machine learning can do for game theory What game theory can do for machine learning
ALGORITHMS VS. ADVERSARIES
No-regret algorithm log T ? find adversarial c benign class of c smaller regret
More generally…
GENERATIVE ADVERSARIAL NETWORKS
Learning generative models fake images!
Learning generative models fake images!
Learning generative models Training data: real face images novel / fake Learn generative model G: random seeds face images
Learning generative models novel / fake
Play the zero-sum game fake Still not an easy task! G, D: deep neural nets. real huge action sets
- Jiitter
- Nadleśnictwo orneta
- What is the new twist in the hunger games chapter 13
- Types of games outdoor
- Hunger games film study
- Cuadro comparativo e-learning b-learning m-learning
- Topic sentence sandwich
- Academia de baile bailarte cali valle del cauca
- Ejemplo de un dilema moral
- Academia olimpica romana
- Colegio academia de humanidades
- Slow academia
- Academia tec
- Academia santa rosa
- Academia santa rosa de lima
- Academia mexicana de derechos humanos, a.c.
- Master psihologie iasi
- Built in nyc
- Villa macul academia
- Triple ciego
- Academia do sucesso
- Academia del exito atomy
- Carajo real academia
- Academia
- Primer academia
- Queratina academia
- Academia militar mariscal sucre
- Insulina academia
- Gravīras nospiedums
- Organigrama de una academia
- Liceo villa macul academia
- "academia international"
- Academia cartagena99