Are Individuals Fickle-Minded?

Game theory has been used to model large-scale social events — such as constitutional law, democratic stability, standard setting, gender roles, social movements, communication, markets, the selection of officials by means of elections, coalition formation, resource allocation, distribution of goods, and war — as the aggregate result of individual choices in interdependent decision-making. Game theory in this way assumes methodological individualism. The widespread observation that game theory predictions do not in general match observation has led to many attempts to repair game theory by creating behavioral game theory, which adds corrective terms to the game theoretic predictions in the hope of making predictions that better match observations. But for game theory to be useful in making predictions, we must be able to generalize from an individual’s behavior in one situation to that individual’s behavior in very closely similar situations. In other words, behavioral game theory needs individuals to be reasonably consistent in action if the theory is to have predictive power. We argue on the basis of experimental evidence that the assumption of such consistency is unwarranted. More realistic models of individual agents must be developed that acknowledge the variance in behavior for a given individual

Gender Differences and Digital Learning Games – One Size Does not fit all

The intrinsic motivation demonstrated towards digital games provides the opportunity for its use as a learning tool irrespective of gender differences. This has resulted in the combination of the motivation of games with curricular content referred to as Digital Game-Based Learning. While some related studies have argued that there are no gender differences in the motivational appeal of digital educational games, others present an opposing view. This paper reports the result of an investigation into the motivational appeal of digital educational games for 11-14 years old girls and boys. There is evidence that this age group is pivotal to the shrinking pipeline phenomenon in which fewer females progressively engage with computer science education and careers. The investigation involved a two stage study composed of a qualitative exploratory study, which identified the key criteria for the successful appeal of some digital entertainment games to young girls and boys and a main study. The main study generate both qualitative and quantitative data to further investigate the motivational appeal of digital educational games for learning basic computer science concepts for both girls and boys of age 11-14 years old. For the main study, two experimental games for learning basic computer science concepts were created based on the key criteria identified from the exploratory study. The first included the game characteristics that appeared to support the motivational appeal of the girls. The second game was antithetical to the first. Both genders from the participating population engaged with both games and online questionnaires were used to capture data on their perception of both games. The outcome of the investigation which involved 304 participants (girls = 152 and boys =152) from Southeast England, United Kingdom provided the empirical evidence in support of the argument that there are gender differences in the motivational appeal of digital educational game characteristics which can either support or thwart motivation i.e. one size does not fit all. The result of this investigation should support educationists, researchers and digital educational game designers in having an inclusive approach towards the creation of digital educational games for learning

One-Counter Stochastic Games

We study the computational complexity of basic decision problems for one-counter simple stochastic games (OC-SSGs), under various objectives. OC-SSGs are 2-player turn-based stochastic games played on the transition graph of classic one-counter automata. We study primarily the termination objective, where the goal of one player is to maximize the probability of reaching counter value 0, while the other player wishes to avoid this. Partly motivated by the goal of understanding termination objectives, we also study certain "limit" and "long run average" reward objectives that are closely related to some well-studied objectives for stochastic games with rewards. Examples of problems we address include: does player 1 have a strategy to ensure that the counter eventually hits 0, i.e., terminates, almost surely, regardless of what player 2 does? Or that the liminf (or limsup) counter value equals infinity with a desired probability? Or that the long run average reward is >0 with desired probability? We show that the qualitative termination problem for OC-SSGs is in NP intersection coNP, and is in P-time for 1-player OC-SSGs, or equivalently for one-counter Markov Decision Processes (OC-MDPs). Moreover, we show that quantitative limit problems for OC-SSGs are in NP intersection coNP, and are in P-time for 1-player OC-MDPs. Both qualitative limit problems and qualitative termination problems for OC-SSGs are already at least as hard as Condon's quantitative decision problem for finite-state SSGs.Comment: 20 pages, 1 figure. This is a full version of a paper accepted for publication in proceedings of FSTTCS 201

A Smart Game for Data Transmission and Energy Consumption in the Internet of Things

The current trend in developing smart technology for the Internet of Things (IoT) has motivated a lot of research interest in optimizing data transmission or minimizing energy consumption, but with little evidence of proposals for achieving both objectives in a single model. Using the concept of game theory, we develop a new MAC protocol for IEEE 802.15.4 and IoT networks in which we formulate a novel expression for the players' utility function and establish a stable Nash equilibrium (NE) for the game. The proposed IEEE 802.15.4 MAC protocol is modeled as a smart game in which analytical expressions are derived for channel access probability, data transmission probability, and energy used. These analytical expressions are used in formulating an optimization problem (OP) that maximizes data transmission and minimizes energy consumption by nodes. The analysis and simulation results suggest that the proposed scheme is scalable and achieves better performance in terms of data transmission, energy-efficiency, and longevity, when compared with the default IEEE 802.15.4 access mechanism.Peer reviewe

On an Evolutionary Foundation of Neuroeconomics

Neuroeconomics focuses on brain imaging studies mapping neural responses to choice behavior. Economic theory is concerned with choice behavior but it is silent on neural activities. We present a game theoretic model in which players are endowed with an additional structure - a simple "nervous system" - and interact repeatedly in changing games. The nervous system constrains information processing functions and behavioral functions. By reinterpreting results from evolutionary game theory (Germano, 2007), we suggest that nervous systems can develop to "function well" in exogenously changing strategic environments. We present an example indicating that an analogous conclusion fails if players can influence endogenously their environment.Neuroeconomic theory; Evolutionary game theory; Learning in games