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Game Theory and Computer Networks: a useful combination? Christos Samaras, COMNET Group, DUTH

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Game Theory: general theory of rational behavior What constitutes/characterizes a game: - group of players (more than 1 decision-maker) - interaction (interdependence: when a player acts, at least one other player is affected) - strategic (a player takes this interdependence into account before deciding what action to take) - rational (a player chooses her best action)

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consider... some players that simultaneously transmit data (a transport entity = a player) they all share the same network channel (low bandwidth) each player chooses a strategy (e.g. conservative/aggressive behavior) every player is rational Let the game begin ! (but... what are the rules of the game?)

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GAME RULES WHO…WHEN… HOW MUCH… WHAT… is playing (group of players) they are playing (available strategies) each player gets to play (order of playing) they stand to gain or lose

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In game theory it is standard to assume COMMON KNOWLEDGE about the rules

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Visiting again our Internet Game, we have some answers: WHO… ? a transport protocol (= an Internet player) WHAT… ? transmit data (aggressively, conservatively, etc.) WHEN… ? no turns, no rounds… (asynchronously) HOW MUCH… ? gain? lose? Utility Function

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Utility Function (= Payoff Function) …specifies the PAYOFF to a player for every possible strategy combination that he – and the others – might pick. (Internet game: a player's payoff depends on his transmission rate and congestion/delay experienced by his packets) The independent variable in such a function is the player’s strategy. So… what’s the best strategy? Strategy_3

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Solutions... (to a game) Dominant Strategy: strategy S i strongly dominates all other strategies of player i if the payoff to S i is strictly greater than the payoff to any other strategy, regardless of which strategy is chosen by the other player(s). (the best strategy) Dominance Solvability: a strategy S1 is dominated by another strategy S2, if the latter does at least as well as S1 against every strategy of the other players, and against some it does strictly better. (try to find an undominated strategy: it’s a good choice) Nash Equilibrium: a player selects the best strategy (which yields him the highest payoff possible) assuming what his opponents' strategy choice will be. A strategy combination (which comprises a strategy choice for each player) is a Nash equilibrium if each player’s strategy is a best response against his opponents’ choices in that combination.

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Game Variations Extensive Games... players take turns; the possible actions a player can take on his turn depend on the previous actions taken by himself and the other players Repeated Games... a standard game that is played repeatedly Signaling Games... the players can signal each other and share some of their intended play, or private information Bargaining Games... includes states for making binding offers which the other player(s) can reject or accept Games with Incomplete Information... the players have to take actions without having full information on the different factors that influence their utility

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Internet Equilibrium Game: Internet congestion control Some characteristics of the “Internet Game”: - repeated games - distributed environment - conditions and number of players change rapidly Internet equilibrium is not achieved by rational contemplation but by interaction and adaptation...in an environment where conditions (and player populations) change rapidly (and in which changes in strategies incur costs).

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Nash equilibrium … is not (always) the solution to look for Why? efficiency, fairness are NOT GUARANTEED by Nash equilibrium actually, a standard solution concept (like Nash equilibrium) DOES NOT APPLY to an asynchronous and distributed environment like the Internet MORE SOPHISTICATED concepts of equilibria are more appropriate for the context of the Internet

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A "perfect" design: Given desired goals, design a game (strategy sets and payoffs) in such a clever way that individual players, motivated solely by self-interest, end up achieving the designer's goals.

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A (more or less) tangible goal: Develop a reasonably faithful game-theoretic model of Internet congestion control for which (an approximation of) TCP/IP is a Nash equilibrium. To be defined... - PAYOFF to each player (for instance: a player tries more but gains less) - what kind of PENALTY for selfish/greedy players? - WHO is responsible for penalizing a player? and HOW? (network: regulating role?) - desired GOALS: 1. for the network/Internet (better bandwidth utilization? lower delays provision? fairness above all?) 2. for the players (better throughput/goodput? less packet losses/packet retransmissions? smooth data transfer?)

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Some facts about the Internet Congestion Game not a "common knowledge" game asynchronous, repeated games in a distributed environment payoff function not known (nor the payoff functions of the opponents) little a priori info (about other players/payoff function(s)) little or no knowledge of the underlying network topology conditions change constantly

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what next? The aforementioned scheme calls for network rules and actions (which will motivate the behavior of players)...in this context we have selected TCP Vegas (throughput estimation mechanism) remarks / ideas for proceeding: - network/Internet should not be vulnerable to greedy users - Nash equilibria are not necessarily achieved (as a result of learning) - nature of learning and convergence in the Internet - reasonable "learning" behavior

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Any questions?

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Nash equilibrium Nash equilibrium is defined in terms of strategies, not payoffs Every player is best responding simultaneously (everyone optimizes) This.

Nash equilibrium Nash equilibrium is defined in terms of strategies, not payoffs Every player is best responding simultaneously (everyone optimizes) This.

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