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Social Network Games Krzysztof R. Apt CWI and University of - PowerPoint PPT Presentation

Social Network Games Krzysztof R. Apt CWI and University of Amsterdam Based on joint works with Evangelos Markakis and Sunil Simon Social Networks Facebook, Hyves, LinkedIn, Nasza Klasa, . . . Krzysztof R. Apt Social Network Games But


  1. Social Network Games Krzysztof R. Apt CWI and University of Amsterdam Based on joint works with Evangelos Markakis and Sunil Simon

  2. Social Networks Facebook, Hyves, LinkedIn, Nasza Klasa, . . . Krzysztof R. Apt Social Network Games

  3. But also . . . An area with links to sociology (spread of patterns of social behaviour) economics (effects of advertising, emergence of ‘bubbles’ in financial markets, . . . ), epidemiology (epidemics), computer science (complexity analysis), mathematics (graph theory). Krzysztof R. Apt Social Network Games

  4. Example (From D. Easley and J. Kleinberg, 2010). Collaboration of mathematicians centered on Paul Erd˝ os. Drawing by Ron Graham. Krzysztof R. Apt Social Network Games

  5. The model Social network ([Apt, Markakis ’11, ’14]) Weighted directed graph: G = ( V , → , w ), where V : a finite set of agents, w ij ∈ (0 , 1]: weight of the edge i → j . Products: A finite set of products P . Product assignment: P : V → 2 P \ {∅} ; assigns to each agent a non-empty set of products. Threshold function: θ ( i , t ) ∈ (0 , 1], for each agent i and product t ∈ P ( i ). Neighbours of node i : { j ∈ V | j → i } . Source nodes: Agents with no neighbours. Krzysztof R. Apt Social Network Games

  6. The associated strategic game Interaction between agents: Each agent i can adopt a product from the set P ( i ) or choose not to adopt any product ( t 0 ). Social network games Players: Agents in the network. Strategies: Set of strategies for player i is P ( i ) ∪ { t 0 } . Payoff: Fix c > 0. Given a joint strategy s and an agent i , Krzysztof R. Apt Social Network Games

  7. The associated strategic game Interaction between agents: Each agent i can adopt a product from the set P ( i ) or choose not to adopt any product ( t 0 ). Social network games Players: Agents in the network. Strategies: Set of strategies for player i is P ( i ) ∪ { t 0 } . Payoff: Fix c > 0. Given a joint strategy s and an agent i , � 0 if s i = t 0 ◮ if i ∈ source ( S ), p i ( s ) = if s i ∈ P ( i ) c Krzysztof R. Apt Social Network Games

  8. The associated strategic game Interaction between agents: Each agent i can adopt a product from the set P ( i ) or choose not to adopt any product ( t 0 ). Social network games Players: Agents in the network. Strategies: Set of strategies for player i is P ( i ) ∪ { t 0 } . Payoff: Fix c > 0. Given a joint strategy s and an agent i , � 0 if s i = t 0 ◮ if i ∈ source ( S ), p i ( s ) = if s i ∈ P ( i ) c ◮ if i �∈ source ( S ), p i ( s ) =  0 if s i = t 0  � w ji − θ ( i , t ) if s i = t , for some t ∈ P ( i )  j ∈N t i ( s ) N t i ( s ): the set of neighbours of i who adopted in s the product t . P Krzysztof R. Apt Social Network Games

  9. Example {•} 4 0.4 {• , •} 1 0.5 0.5 {• , •} {• , •} 3 2 0.5 0.4 0.4 6 5 {•} {•} Threshold is 0 . 3 for all the players. P = {• , • , •} Krzysztof R. Apt Social Network Games

  10. Example {•} 4 0.4 {• , •} 1 0.5 0.5 Payoff: p 4 ( s ) = p 5 ( s ) = p 6 ( s ) = c {• , •} {• , •} 3 2 0.5 0.4 0.4 6 5 {•} {•} Threshold is 0 . 3 for all the players. P = {• , • , •} Krzysztof R. Apt Social Network Games

  11. Example {•} 4 0.4 {• , •} 1 0.5 0.5 Payoff: p 4 ( s ) = p 5 ( s ) = p 6 ( s ) = c {• , •} {• , •} 3 2 0.5 p 1 ( s ) = 0 . 4 − 0 . 3 = 0 . 1 0.4 0.4 6 5 {•} {•} Threshold is 0 . 3 for all the players. P = {• , • , •} Krzysztof R. Apt Social Network Games

  12. Example {•} 4 0.4 {• , •} 1 0.5 0.5 Payoff: p 4 ( s ) = p 5 ( s ) = p 6 ( s ) = c {• , •} {• , •} 3 2 0.5 p 1 ( s ) = 0 . 4 − 0 . 3 = 0 . 1 0.4 0.4 p 2 ( s ) = 0 . 5 − 0 . 3 = 0 . 2 6 5 p 3 ( s ) = 0 . 4 − 0 . 3 = 0 . 1 {•} {•} Threshold is 0 . 3 for all the players. P = {• , • , •} Krzysztof R. Apt Social Network Games

  13. Social network games Properties Graphical game: The payoff for each player depends only on the choices made by his neighbours. Join the crowd property: The payoff of each player weakly increases if more players choose the same strategy. Krzysztof R. Apt Social Network Games

  14. Does Nash equilibrium always exist? {•} 4 0.4 {• , •} 1 0.5 0.5 {• , •} {• , •} 3 2 0.5 0.4 0.4 6 5 {•} {•} Threshold is 0 . 3 for all the players. Krzysztof R. Apt Social Network Games

  15. Does Nash equilibrium always exist? {•} 4 0.4 {• , •} 1 Observation: No player has the 0.5 0.5 incentive to choose t 0 . {• , •} {• , •} 3 2 Source nodes can ensure a 0.5 payoff of c > 0. 0.4 0.4 6 5 Each player on the cycle can ensure a payoff of at least 0 . 1. {•} {•} Threshold is 0 . 3 for all the players. Krzysztof R. Apt Social Network Games

  16. Does Nash equilibrium always exist? {•} ( • , • , • ) 4 0.4 {• , •} 1 Observation: No player has the 0.5 0.5 incentive to choose t 0 . {• , •} {• , •} 3 2 Source nodes can ensure a 0.5 payoff of c > 0. 0.4 0.4 6 5 Each player on the cycle can ensure a payoff of at least 0 . 1. {•} {•} Threshold is 0 . 3 for all the players. Krzysztof R. Apt Social Network Games

  17. Does Nash equilibrium always exist? Best response dynamics {•} ( • , • , • ) ( • , • , • ) ( • , • , • ) 4 0.4 ( • , • , • ) ( • , • , • ) ( • , • , • ) {• , •} 1 Observation: No player has the 0.5 0.5 incentive to choose t 0 . {• , •} {• , •} 3 2 Source nodes can ensure a 0.5 payoff of c > 0. 0.4 0.4 6 5 Each player on the cycle can ensure a payoff of at least 0 . 1. {•} {•} Reason: Players keep switching Threshold is 0 . 3 for all the players. between the products. Krzysztof R. Apt Social Network Games

  18. Nash equilibrium Question: Given a social network S , what is the complexity of deciding whether G ( S ) has a Nash equilibrium? Krzysztof R. Apt Social Network Games

  19. Nash equilibrium Question: Given a social network S , what is the complexity of deciding whether G ( S ) has a Nash equilibrium? Answer: NP-complete. Krzysztof R. Apt Social Network Games

  20. Nash equilibrium Question: Given a social network S , what is the complexity of deciding whether G ( S ) has a Nash equilibrium? Answer: NP-complete. The PARTITION problem Input: n positive rational numbers ( a 1 , . . . , a n ) such that � i a i = 1. Question: Is there a set S ⊆ { 1 , 2 , . . . , n } such that a i = 1 � � a i = 2 . i ∈ S i �∈ S Krzysztof R. Apt Social Network Games

  21. Hardness Reduction: Given an instance of the PARTITION problem P = ( a 1 , . . . , a n ) , construct a network S ( P ) such that there is a solution to P iff there is a Nash equilibrium in S ( P ).

  22. Hardness Reduction: Given an instance of the PARTITION problem P = ( a 1 , . . . , a n ) , construct a network S ( P ) such that there is a solution to P iff there is a Nash equilibrium in S ( P ). {• ′ } {•} 4 ′ 4 0 . 4 0 . 4 {• ′ , • ′ } {• , •} 1 ′ 1 0 . 5 0 . 5 0 . 5 0 . 5 {• ′ , • ′ } {• , •} {• ′ , • ′ } {• , •} 3 2 3 ′ 2 ′ 0 . 5 0 . 5 0 . 4 0 . 4 0 . 4 0 . 4 6 5 6 ′ 5 ′ {• ′ } {• ′ } {•} {•} Krzysztof R. Apt Social Network Games

  23. Hardness Reduction: Given an instance of the PARTITION problem P = ( a 1 , . . . , a n ) , construct a network S ( P ) such that there is a solution to P iff there is a Nash equilibrium in S ( P ). {• , • ′ } {• , • ′ } {• , • ′ } · · · i 1 i 2 i n {• ′ } {•} 4 ′ 4 0 . 4 0 . 4 {• ′ , • ′ } {• , •} 1 ′ 1 0 . 5 0 . 5 0 . 5 0 . 5 {• ′ , • ′ } {• , •} {• ′ , • ′ } {• , •} 3 2 3 ′ 2 ′ 0 . 5 0 . 5 0 . 4 0 . 4 0 . 4 0 . 4 6 5 6 ′ 5 ′ {• ′ } {• ′ } {•} {•} Krzysztof R. Apt Social Network Games

  24. Hardness Reduction: Given an instance of the PARTITION problem P = ( a 1 , . . . , a n ) , construct a network S ( P ) such that there is a solution to P iff there is a Nash equilibrium in S ( P ). {• , • ′ } {• , • ′ } {• , • ′ } · · · i 1 i 2 i n a 1 {• ′ } {•} 4 ′ 4 a 1 0 . 4 0 . 4 {• ′ , • ′ } {• , •} 1 ′ 1 0 . 5 0 . 5 0 . 5 0 . 5 {• ′ , • ′ } {• , •} {• ′ , • ′ } {• , •} 3 2 3 ′ 2 ′ 0 . 5 0 . 5 0 . 4 0 . 4 0 . 4 0 . 4 6 5 6 ′ 5 ′ {• ′ } {• ′ } {•} {•} Krzysztof R. Apt Social Network Games

  25. Hardness Reduction: Given an instance of the PARTITION problem P = ( a 1 , . . . , a n ) , construct a network S ( P ) such that there is a solution to P iff there is a Nash equilibrium in S ( P ). {• , • ′ } {• , • ′ } {• , • ′ } · · · i 1 i 2 i n a 1 a 2 a 2 {• ′ } {•} 4 ′ 4 a 1 0 . 4 0 . 4 {• ′ , • ′ } {• , •} 1 ′ 1 0 . 5 0 . 5 0 . 5 0 . 5 {• ′ , • ′ } {• , •} {• ′ , • ′ } {• , •} 3 2 3 ′ 2 ′ 0 . 5 0 . 5 0 . 4 0 . 4 0 . 4 0 . 4 6 5 6 ′ 5 ′ {• ′ } {• ′ } {•} {•} Krzysztof R. Apt Social Network Games

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