COOPERATION AND COMPETITION: LEARNING OF STRATEGIES AND EVOLUTION OF PREFERENCES IN PRISONERS' DILEMMA AND HAWK-DOVE GAMES

2005 ◽  
Vol 07 (04) ◽  
pp. 443-459 ◽  
Author(s):  
ALEX POSSAJENNIKOV
Keyword(s):  
Incomplete Information ◽  
Complete Information ◽  
Symmetric Equilibrium ◽  
Cooperation And Competition ◽  
Strategy Profile ◽  
Prisoners Dilemma ◽  
Evolution Of Preferences ◽  
Reciprocal Preferences

By means of simulations I investigate a two-speed dynamic on strategies and preferences in prisoners' dilemmas and in hawk-dove games. Players learn strategies according to their preferences while evolution leads to a change in the preference composition. With complete information about the preferences of the opponent, cooperation in prisoners' dilemmas is achieved temporarily, with "reciprocal" preferences. In hawk-dove games, a symmetric correlated strategy profile is played that does not place any weight on mutual restraint. Among preferences only "hawkish" preferences and "selfish" preferences survive. With incomplete information, the symmetric equilibrium of the game is played. In prisoners' dilemmas only "selfish" and "reciprocal" preferences survive. In hawk-dove games all preferences are present in the medium run.

scholarly journals Spillovers and R&D Incentive under Incomplete Information

2018 ◽  
Vol 6 (1-2) ◽  
pp. 50-65 ◽  
Author(s):  
Rittwik Chatterjee ◽  
Srobonti Chattopadhyay ◽  
Tarun Kabiraj
Keyword(s):  
Distribution Function ◽  
Incomplete Information ◽  
Private Information ◽  
Complete Information ◽  
Jel Classification ◽  
General Distribution ◽  
Two Stage ◽  
Stage Game ◽  
Alternative Scenarios

Spillovers of R&D outcome affect the R&D decision of a firm. The present paper discusses the R&D incentives of a firm when the extent of R&D spillover is private information to each firm. We construct a two-stage game involving two firms when the firms first decide simultaneously whether to invest in R&D or not, then they compete in quantity. Assuming general distribution function of firm types we compare R&D incentives of firms under alternative scenarios based on different informational structures. The paper shows that while R&D spillovers reduce R&D incentives under complete information unambiguously, however, it can be larger under incomplete information. JEL Classification: D43, D82, L13, O31

scholarly journals Distance Metrics of D Numbers

2020 ◽  
Author(s):  
Liguo Fei ◽  
Yuqiang Feng
Keyword(s):  
Number Theory ◽  
Incomplete Information ◽  
Distance Function ◽  
Distance Measure ◽  
Complete Information ◽  
Belief Function ◽  
Distance Metrics ◽  
Modeling Methods ◽  
The Difference ◽  
D Numbers

Belief function has always played an indispensable role in modeling cognitive uncertainty. As an inherited version, the theory of D numbers has been proposed and developed in a more efficient and robust way. Within the framework of D number theory, two more generalized properties are extended: (1) the elements in the frame of discernment (FOD) of D numbers do not required to be mutually exclusive strictly; (2) the completeness constraint is released. The investigation shows that the distance function is very significant in measuring the difference between two D numbers, especially in information fusion and decision. Modeling methods of uncertainty that incorporate D numbers have become increasingly popular, however, very few approaches have tackled the challenges of distance metrics. In this study, the distance measure of two D numbers is presented in cases, including complete information, incomplete information, and non-exclusive elements

Incomplete Information in Multidimensional Databases

2003 ◽  
pp. 282-309 ◽  
Author(s):  
Cirtis E. Dyreson ◽  
Torben Bach Pedersen ◽  
Christian S. Jensen
Keyword(s):  
Incomplete Information ◽  
Complete Information ◽  
Multidimensional Data ◽  
Uncertain Information ◽  
Real World Data ◽  
Multidimensional Database ◽  
Simple Strategy ◽  
Multidimensional Databases ◽  
Derived Data ◽  
Base Data

While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information in base data, derived data, and dimensions. This chapter presents several strategies for managing incomplete information in multidimensional databases. Which strategy to use is dependent on the kind of incomplete information present, and also on where it occurs in the multidimensional database. A relatively simple strategy is to replace incomplete information with appropriate, complete information. The advantage of this strategy is that all multidimensional databases can manage complete information. Other strategies require more substantial changes to the multidimensional database. One strategy is to reflect the incompleteness in computed aggregates, which is possible only if the multidimensional database allows incomplete values in its hierarchies. Another strategy is to measure the amount of incompleteness in aggregated values by tallying how much uncertain information went into their production.

AMERICAN OPTIONS AND INCOMPLETE INFORMATION

2019 ◽  
Vol 22 (06) ◽  
pp. 1950035 ◽  
Author(s):  
ERIK EKSTRÖM ◽  
MARTIN VANNESTÅL
Keyword(s):  
Incomplete Information ◽  
American Options ◽  
Lower Boundary ◽  
Complete Information ◽  
Call Option ◽  
Standard Case ◽  
Underlying Process ◽  
Parameter Values ◽  
American Put

We study the optimal exercise of American options under incomplete information about the drift of the underlying process, and we show that quite unexpected phenomena may occur. In fact, certain parameter values give rise to stopping regions very different from the standard case of complete information. For example, we show that for the American put (call) option it is sometimes optimal to exercise the option when the underlying process reaches an upper (lower) boundary.

scholarly journals A Study of Prisoner’s Dilemma Game Model with Incomplete Information

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Xiuqin Deng ◽  
Jiadi Deng
Keyword(s):  
Incomplete Information ◽  
Hash Table ◽  
Game Problem ◽  
Multiplayer Games ◽  
Total Income ◽  
Bayes Model ◽  
Bayes Formula ◽  
Machine Learning Model ◽  
Prisoners Dilemma ◽  
Novel Method

Prisoners’ dilemma is a typical game theory issue. In our study, it is regarded as an incomplete information game with unpublicized game strategies. We solve our problem by establishing a machine learning model using Bayes formula. The model established is referred to as the Bayes model. Based on the Bayesian model, we can make the prediction of players’ choices to better complete the unknown information in the game. And we suggest the hash table to make improvement in space and time complexity. We build a game system with several types of game strategy for testing. In double- or multiplayer games, the Bayes model is more superior to other strategy models; the total income using Bayes model is higher than that of other models. Moreover, from the result of the games on the natural model with Bayes model, as well as the natural model with TFT model, it is found that Bayes model accrued more benefits than TFT model on average. This demonstrates that the Bayes model introduced in this study is feasible and effective. Therefore, it provides a novel method of solving incomplete information game problem.

Pre-contest Communication Incentives

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Mustafa Yildirim
Keyword(s):  
Incomplete Information ◽  
Complete Information ◽  
Psychological Strength

AbstractTo demonstrate resolution and psychological strength, players often engage in pre-contest communication by publicly stating their desire to win an upcoming contest. Existing explanations for this phenomenon revolve around incomplete information and signaling. In this paper, I offer a complementary explanation that does not rely on signaling. Within a complete information setup, I show that players may have an incentive for pre-contest communication if, in addition to an audience (reputational) cost when the statement does not materialize, the players also incur an audience reward (credibility gain) when the statement materializes.

Strategic Investment under Incomplete Information

2018 ◽  
Vol 18 (2) ◽  
Author(s):  
Mohammad H. Dehghani
Keyword(s):  
Incomplete Information ◽  
The Other ◽  
Investment Strategies ◽  
Symmetric Equilibrium ◽  
Sunk Cost ◽  
Strategic Investment ◽  
First Case ◽  
Investment Cost ◽  
Lower Uncertainty ◽  
First Mover

Abstract This paper studies how hiding sunk cost of investment would affect investment strategies in a duopoly. The investment would improve profit. If this improvement is larger for the first mover than the second mover, this study finds a unique symmetric equilibrium for a subset of such cases. On the other hand, a larger improvement for the second mover results in a class of symmetric equilibria. For the first case, the surplus to sharing information increases with higher volatility of profit flow and lower uncertainty about the investment cost. For the second case, this surplus grows with both mentioned types of uncertainty.

Game Theory and Other Modeling Approaches

2018 ◽  
Author(s):  
Frank C. Zagare ◽  
Branislav L. Slantchev
Keyword(s):  
Game Theory ◽  
International Relations ◽  
Incomplete Information ◽  
Dynamic Games ◽  
Complete Information ◽  
Third Wave ◽  
Extensive Form ◽  
Interactive Decision Making ◽  
The Game Theory ◽  
Almost All

Game theory is the science of interactive decision making. It has been used in the field of international relations (IR) for over 50 years. Almost all of the early applications of game theory in international relations drew upon the theory of zero-sum games, but the first generation of applications was also developed during the most intense period of the Cold War. The theoretical foundations for the second wave of the game theory literature in international relations were laid by a mathematician, John Nash, a co-recipient of the 1994 Nobel Prize in economics. His major achievement was to generalize the minimax solution which emerged from the first wave. The result is the now famous Nash equilibrium—the accepted measure of rational behavior in strategic form games. During the third wave, from roughly the early to mid-1980s to the mid-1990s, there was a distinct move away from static strategic form games toward dynamic games depicted in extensive form. The assumption of complete information also fell by the wayside; games of incomplete information became the norm. Technical refinements of Nash’s equilibrium concept both encouraged and facilitated these important developments. In the fourth and final wave, which can be dated, roughly, from around the middle of the 1990s, extensive form games of incomplete information appeared regularly in the strategic literature. The fourth wave is a period in which game theory was no longer considered a niche methodology, having finally emerged as a mainstream theoretical tool.

Implementation Errors and Incomplete Information

2018 ◽  
Author(s):  
Rafael Portillo ◽  
Filiz Unsal ◽  
Stephen O’Connell ◽  
Catherine Pattillo
Keyword(s):  
Monetary Policy ◽  
Interest Rates ◽  
Incomplete Information ◽  
Low Income ◽  
Complete Information ◽  
Structural Features ◽  
New Keynesian ◽  
Low Income Countries ◽  
Keynesian Model ◽  
Policy Frameworks

This chapter shows that limited effects of monetary policy can reflect shortcomings of existing policy frameworks in low-income countries rather than (or in addition to) the structural features often put forward in policy and academic debates. The chapter focuses on two pervasive issues: lack of effective frameworks for implementing policy, so that short-term interest rates display considerable unintended volatility, and poor communication about policy intent. The authors introduce these features into an otherwise standard New Keynesian model with incomplete information. Implementation errors result from insufficient accommodation to money demand shocks, creating a noisy wedge between actual and intended interest rates. The representative private agent must then infer policy intentions from movements in interest rates and money. Under these conditions, even exogenous and persistent changes in the stance of monetary policy can have weak effects, even when the underlying transmission (as might be observed under complete information) is strong.

scholarly journals Linkboost: A Link Prediction Algorithm to Solve the Problem of Network Vulnerability in Cases Involving Incomplete Information

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chengfeng Jia ◽  
Jie Ma ◽  
Qi Liu ◽  
Yu Zhang ◽  
Hua Han
Keyword(s):  
Incomplete Information ◽  
Complete Information ◽  
Prediction Algorithm ◽  
Network Vulnerability ◽  
Limited Information ◽  
Research Attention ◽  
Network Information ◽  
Imbalanced Class Distribution ◽  
High Degree ◽  
Attack Strategy

The vulnerability of network information systems has attracted considerable research attention in various domains including financial networks, transportation networks, and infrastructure systems. To comprehensively investigate the network vulnerability, well-designed attack strategies are necessary. However, it is difficult to formulate a global attack strategy as the complete information of the network is usually unavailable. To overcome this limitation, this paper proposes a novel prediction algorithm named Linkboost, which, by predicting the hidden edges of the network, can complement the seemingly missing but potentially existing connections of the network with limited information. The key aspect of this algorithm is that it can deal with the imbalanced class distribution present in the network data. The proposed approach was tested on several types of networks, and the experimental results indicated that the proposed algorithm can successfully enhance the destruction rate of the network even with incomplete information. Furthermore, when the proportion of the missing information is relatively small, the proposed attack strategy relying on the high degree nodes performs even better than that with complete information. This finding suggests that the nodes important to the network structure and connectivity can be more easily identified by the links added by Linkboost. Therefore, the use of Linkboost can provide useful insight into the operation guidance and design of a more effective attack strategy.

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