Opponent's Actions Research Articles

Modeling of relationships between producer and consumer: The impact of advanced production equipment

Subject. The article discusses the influence of advanced production equipment on modeling the relationship between manufacturer and consumer. Objectives. The aim is to assess the impact of the organization's existing production facilities, created on the basis of modern machine tools, on the possibility of building mutually beneficial relations between the manufacturer and the buyer of products. Methods. The research rests on methods of economic and mathematical modeling, in particular, the game theory tools. Results. We formulated a meaningful model of idealized interaction between the parties in the process of concluding a contract for production and purchase of goods, offered a model of positional game of the parties with complete information, in which the participants consistently make decisions with understanding the opponent's previous actions. The analysis of the constructed model enabled to determine the situation of balance between the parties and demonstrate a decrease in consumer's influence on the results of the interaction, due to flexibility and adaptability of production capabilities of the manufacturing organization. Conclusions. The findings demonstrate the influence of aspect associated with the involvement of modern production equipment on the consumer's willingness to establish mutually beneficial relationships with the manufacturing organization. This provides a basis for subsequent implementation of partnership within the framework of relationship marketing.

Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning.

The striatum is required for normal action selection, movement, and sensorimotor learning. Although action-specific striatal ensembles have been well documented, it is not well understood how these ensembles are formed and how their dynamics may evolve throughout motor learning. Here we used longitudinal 2-photon Ca 2+ imaging of dorsal striatal neurons in head-fixed mice as they learned to self-generate locomotion. We observed a significant activation of both direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs, respectively) during early locomotion bouts and sessions that gradually decreased over time. For dSPNs, onset- and offset-ensembles were gradually refined from active motion-nonspecific cells. iSPN ensembles emerged from neurons initially active during opponent actions before becoming onset- or offset-specific. Our results show that as striatal ensembles are progressively refined, the number of active nonspecific striatal neurons decrease and the overall efficiency of the striatum information encoding for learned actions increases.

Persistence in repeated games encourages the evolution of spite

Social behavior is divided into four types: altruism, spite, mutualism, and selfishness. The former two are costly to the actor; therefore, from the perspective of natural selection, their existence can be regarded as mysterious. One potential setup which encourages the evolution of altruism and spite is repeated interaction. Players can behave conditionally based on their opponent's previous actions in the repeated interaction. On the one hand, the retaliatory strategy (who behaves altruistically when their opponent behaved altruistically and behaves non-altruistically when the opponent player behaved non-altruistically) is likely to evolve when players choose altruistic or selfish behavior in each round. On the other hand, the anti-retaliatory strategy (who is spiteful when the opponent was not spiteful and is not spiteful when the opponent player was spiteful) is likely to evolve when players opt for spiteful or mutualistic behavior in each round. These successful conditional behaviors can be favored by natural selection. Here, we notice that information on opponent players’ actions is not always available. When there is no such information, players cannot determine their behavior according to their opponent's action. By investigating the case of altruism, a previous study (Kurokawa, 2017, Mathematical Biosciences, 286, 94–103) found that persistent altruistic strategies, which choose the same action as the own previous action, are favored by natural selection. How, then, should a spiteful conditional strategy behave when the player does not know what their opponent did? By studying the repeated game, we find that persistent spiteful strategies, which choose the same action as the own previous action, are favored by natural selection. Altruism and spite differ concerning whether retaliatory or anti-retaliatory strategies are favored by natural selection; however, they are identical concerning whether persistent strategies are favored by natural selection.

The effect of task load, information reliability and interdependency on anticipation performance

In sport, coaches often explicitly provide athletes with stable contextual information related to opponent action preferences to enhance anticipation performance. This information can be dependent on, or independent of, dynamic contextual information that only emerges during the sequence of play (e.g. opponent positioning). The interdependency between contextual information sources, and the associated cognitive demands of integrating information sources during anticipation, has not yet been systematically examined. We used a temporal occlusion paradigm to alter the reliability of contextual and kinematic information during the early, mid- and final phases of a two-versus-two soccer anticipation task. A dual-task paradigm was incorporated to investigate the impact of task load on skilled soccer players’ ability to integrate information and update their judgements in each phase. Across conditions, participants received no contextual information (control) or stable contextual information (opponent preferences) that was dependent on, or independent of, dynamic contextual information (opponent positioning). As predicted, participants used reliable contextual and kinematic information to enhance anticipation. Further exploratory analysis suggested that increased task load detrimentally affected anticipation accuracy but only when both reliable contextual and kinematic information were available for integration in the final phase. This effect was observed irrespective of whether the stable contextual information was dependent on, or independent of, dynamic contextual information. Findings suggest that updating anticipatory judgements in the final phase of a sequence of play based on the integration of reliable contextual and kinematic information requires cognitive resources.

Decision-Making With Speculative Opponent Models.

Opponent modeling has proven effective in enhancing the decision-making of the controlled agent by constructing models of opponent agents. However, existing methods often rely on access to the observations and actions of opponents, a requirement that is infeasible when such information is either unobservable or challenging to obtain. To address this issue, we introduce distributional opponent-aided multiagent actor-critic (DOMAC), the first speculative opponent modeling algorithm that relies solely on local information (i.e., the controlled agent's observations, actions, and rewards). Specifically, the actor maintains a speculated belief about the opponents using the tailored speculative opponent models that predict the opponents' actions using only local information. Moreover, DOMAC features distributional critic models that estimate the return distribution of the actor's policy, yielding a more fine-grained assessment of the actor's quality. This thus more effectively guides the training of the speculative opponent models that the actor depends upon. Furthermore, we formally derive a policy gradient theorem with the proposed opponent models. Extensive experiments under eight different challenging multiagent benchmark tasks within the MPE, Pommerman, and starcraft multiagent challenge (SMAC) demonstrate that our DOMAC successfully models opponents' behaviors and delivers superior performance against state-of-the-art (SOTA) methods with a faster convergence speed.

Sports competition tactical analysis model of cross-modal transfer learning intelligent robot based on Swin Transformer and CLIP.

This paper presents an innovative Intelligent Robot Sports Competition Tactical Analysis Model that leverages multimodal perception to tackle the pressing challenge of analyzing opponent tactics in sports competitions. The current landscape of sports competition analysis necessitates a comprehensive understanding of opponent strategies. However, traditional methods are often constrained to a single data source or modality, limiting their ability to capture the intricate details of opponent tactics. Our system integrates the Swin Transformer and CLIP models, harnessing cross-modal transfer learning to enable a holistic observation and analysis of opponent tactics. The Swin Transformer is employed to acquire knowledge about opponent action postures and behavioral patterns in basketball or football games, while the CLIP model enhances the system's comprehension of opponent tactical information by establishing semantic associations between images and text. To address potential imbalances and biases between these models, we introduce a cross-modal transfer learning technique that mitigates modal bias issues, thereby enhancing the model's generalization performance on multimodal data. Through cross-modal transfer learning, tactical information learned from images by the Swin Transformer is effectively transferred to the CLIP model, providing coaches and athletes with comprehensive tactical insights. Our method is rigorously tested and validated using Sport UV, Sports-1M, HMDB51, and NPU RGB+D datasets. Experimental results demonstrate the system's impressive performance in terms of prediction accuracy, stability, training time, inference time, number of parameters, and computational complexity. Notably, the system outperforms other models, with a remarkable 8.47% lower prediction error (MAE) on the Kinetics dataset, accompanied by a 72.86-second reduction in training time. The presented system proves to be highly suitable for real-time sports competition assistance and analysis, offering a novel and effective approach for an Intelligent Robot Sports Competition Tactical Analysis Model that maximizes the potential of multimodal perception technology. By harnessing the synergies between the Swin Transformer and CLIP models, we address the limitations of traditional methods and significantly advance the field of sports competition analysis. This innovative model opens up new avenues for comprehensive tactical analysis in sports, benefiting coaches, athletes, and sports enthusiasts alike.

Expert goalkeepers' and coaches' views on anticipation and cue utilisation facing backcourt throws in handball goalkeeping.

Handball goalkeepers have to act under severe spatio-temporal pressure in both standardised (e.g., 7 m penalty) and non-standardised situations (e.g., backcourt throws) which require them to predict action outcome before ball flight is visible. So far, research on goalkeepers' cue utilisation for anticipation of an opponent's action has mainly focused on 7 m throw situations whereas little attention has been paid to the latter, more complex and far more frequently occurring backcourt throw situations. To address this gap, we conducted semi-structured interviews with N = 6 expert handball goalkeepers and goalkeeper coaches [all of whom were (former) expert handball goalkeepers] on anticipation and cue utilisation when facing backcourt throws. The interviews were subsequently transcribed, coded and results were inductively as well as deductively categorised by means of a thematic analysis. Results reveal a variety of kinematic and contextual cues relevant for action anticipation that become available before the game and before or during the throw. Participants reported to use information from the offence (e.g., thrower's jump; opposing team's task distribution) and the defence (e.g., defensive players' strategies, block position) for anticipation in backcourt throw situations. Additionally, we identified several factors that influence cue availability and utilisation. Our findings provide a thorough basis to (a) guide future research that yields questions on kinematic and contextual cue integration and in-situ cue usage as well as (b) inform the development of training programs to foster goalkeepers' anticipatory skill.

Skill-based differences in the impact of opponent exposure during anticipation: the role of context-environment dependency

IntroductionWe examined skilled-based differences in the impact of exposure to an opponent with action tendencies that were either independent of, dependent on, or both independent of and dependent on evolving environmental information during anticipation.MethodsA video-based two-vs.-two soccer task was employed, where 14 expert and 14 novice soccer players had to predict an attacking opponent's imminent actions, before and after exposure to the preceding actions of the opponent.ResultsAnticipation accuracy, number of responses congruent with the opponent's action tendencies, response confidence, and visual dwell time on the opponent in possession increased following opponent exposure, both in experts and novices. When compared to novices, experts demonstrated higher anticipation accuracy, more congruent responses, and greater response confidence. Novices performed at their best when the opponent exhibited action tendencies that were independent of the environment, whereas experts demonstrated their highest performance when the opponent had action tendencies that were both independent of and dependent on unfolding environmental information.DiscussionOur findings provide novel insights into the role of context-environment dependency and support the notion that experts are superior to novices in detecting and utilizing opponents' action tendencies and integrating this information with unfolding environmental information during anticipation.

Linear-quadratic Gaussian Games with Asymmetric Information: Belief Corrections Using the Opponents Actions

Linear-quadratic Gaussian Games with Asymmetric Information: Belief Corrections Using the Opponents Actions

Paolo Odorico, ed. Études byzantines et post-byzantines, Nouvelle série, Tome II (IX), La culture écrite des périphéries byzantines du Moyen-Âge à l’époque moderne

Paolo Odorico, ed. <i>Études byzantines et post-byzantines, Nouvelle série, Tome II (IX), La culture écrite des périphéries byzantines du Moyen-Âge à l’époque moderne</i>

Feigning ignorance for long-term gains

In dynamic strategic interactions, a player who spies the opponent's actions might have incentives to feign ignorance and forgo immediate payoffs so that he can earn higher future payoffs by manipulating the opponent's suspicion. I model and experimentally implement the situation as a two-stage hide-and-seek game. A substantial share of the spying players fails to feign ignorance, despite the empirical suboptimality of the behavior and their largely correct predictions about opponents' suspicion. Subjects are highly heterogeneous in their tendency to feign ignorance and show only moderate learning. The players who are spied on hold empirically correct beliefs and mostly best-respond.

Skill-Based Differences in the Detection and Utilization of Opponent Action Preferences Following Increasing Exposure and Changes in Tendencies.

We examined skill-based differences in the detection and utilization of contextual information over a period of increasing exposure to an opponent's action preferences in soccer. Moreover, we investigated the ability of athletes to adapt to changes in these action preferences over time. In an initial detection phase, the attacking opponent demonstrated a proclivity to either pass or dribble, with these preferences being reversed in a subsequent adaptation phase of the same length. Skilled soccer players showed superior anticipation accuracy across both phases compared with less-skilled counterparts. The skilled participants significantly enhanced their performance over both phases, despite a significant drop in performance immediately following the change in opponent action preferences. In contrast, the less-skilled group only improved over the detection phase. Gaze data revealed that the skilled participants fixated more on kinematically relevant areas, compared with the less-skilled group, and increased the time spent fixating the player "off the ball" following greater volumes of exposure. Our novel findings elaborate on how skilled performers use both action preferences and motion information to anticipate an opponent's impending actions in sport.

OM-TCN: A dynamic and agile opponent modeling approach for competitive games

The non-stationarity of the environment is a crucial challenge for competitive Multi-Agent Reinforcement Learning (MARL) due to the constantly changing opponent policy. Existing schemes are challenging to make the protagonist agent that agilely responds to the opponent’s changes and the resulting non-stationarity, which may inevitably limit their applicability. To address the dynamic opponent policy and adapt to the non-stationary environment continuously, we propose a Temporal Convolutional Network (TCN) model for modeling and predicting opponent behaviors called OM-TCN, and apply it to the widely-used Multi-Agent Deep Deterministic Policies Gradient (MADDPG) algorithm of competitive MARL. In this work, we collect the opponent’s behavior data observed by the protagonist agent and serialize it in granularity of episodes. Then we input the time-series data into OM-TCN for sequence modeling. The OM-TCN learns the historical behaviors of the opponent instead of overfitting to a specific opponent policy, and can make predictions about the opponent’s future actions. Finally, we use predictions of opponent actions in place of the history sampled from the playback buffer, and apply the OM-TCN model to the MADDPG framework for decentralized training. We use the competitive scenario of Multi-agent Particle Environment (MPE) to evaluate the proposed method. Simulation results show that the protagonist agent is able to learn more efficient and stable policy and converge easier than other baselines.

Fictitious Play in Zero-Sum Stochastic Games

We present fictitious play dynamics for stochastic games and analyze its convergence properties in zero-sum stochastic games. Our dynamics involves players forming beliefs on opponent strategy and their own continuation payoff (Q-function), and playing a greedy best response using estimated continuation payoffs. Players update their beliefs from observations of opponent actions. A key property of the learning dynamics is that update of the beliefs on Q-functions occurs at a slower timescale than update of the beliefs on strategies. We show both in the model-based and model-free cases (without knowledge of player payoff functions and state transition probabilities), the beliefs on strategies converge to a stationary mixed Nash equilibrium of the zero-sum stochastic game.

Особливості когнітивної сфери кваліфікованих жінок-боксерок

The purpose of the study is to analyze a set of characteristics of the cognitive sphere of qualified women-boxers in the preparatory and training period. Materials and methods. The article presents the results of a pedagogical experiment that took place at the Koncha-Zaspa sports base with the participation of 19 qualified female boxers. According to the purpose of the study, a comprehensive analysis of the cognitive sphere of combatants in the preparatory period was carried out. The computer complex "Multipsychometer-05" was used to study the features of the cognitive sphere in the preparatory period of women-boxers. To assess the cognitive functions of skilled boxers the techniques of "Regularity" was used to solve verbal problems, which is designed to study the thinking process, including: activity, intelligence, flexibility and RAM and the Domino test to determine nonverbal intellectual abilities. The reliability and validity of the results of scientific research was provided by modern methodological approaches widely used in the theory and methodology of sports training; the use of informative research methods that meet the goals and objectives; a sufficient sample size and the use of modern methods of mathematical statistics in the processing. Results and discussion. The peculiarities of the manifestation of cognitive organization in skilled women-boxers in the conditions of psycho-emotional load were determined. Performing the test task "Establishing patterns" gave us the opportunity to determine verbal intelligence, namely, performance indicators of the function of perception, thinking and attention. Thus, 47.4% (n = 9) of athletes had a low level of verbal intelligence, 31.6% (n = 6) had a medium level and 21.0% (n = 4) had a high level of productivity. The presence of high and medium levels of performance in boxers indicates an increased level of verbal intelligence in women-boxers. The Domino test was used to study nonverbal intellectual abilities. Low values of performance on the Domino test were found in 42.1% (n = 8) of female boxers. The average level was found in 26.4% (n = 5) of athletes, and the remaining 31.6% (n = 6) had a high level of nonverbal intelligence. In most groups boxers showed a high level of nonverbal intelligence, which determines the peculiarities of perception in the process of training to succeed in sports. The remaining female boxers are characterized by nonverbal intellectual abilities. Their intellect is associated with the perception of external factors associated with the opponent's action. They have the ability to quickly respond to situations that develop in a duel. Conclusion. The results of the performance of the verbal test task by athletes, indicate a high degree of expression of the processes of perception and processing of verbal information and an increased level of correctly solved tasks in 52.3% of boxers. In the course of scientific research we found that 52.3% (n = 10) women-boxers have the ability to operate with real objects, images of objects, images, perceive and process information of varying complexity due to sufficient manifestation of nonverbal intelligence

Lawfare as part of hybrid wars: The experience of Ukraine in conflict with Russian Federation

The main objective of the article is to prove the need for the state to have a centralised legal strategy to ensure the protection of state interests on an international level during a hybrid conflict. Centralisation of control and the planning and implementation of legal actions on an international level are core elements of such a strategy, especially for actions under the jurisdiction of international institutions. This article provides an analysis of treaties and of the practice of adjudication in Ukraine during the conflict with the Russian Federation. The findings of the study show that the legal dimension of hybrid conflict has some sub-levels: legal actions of states in hybrid conflicts taken at interstate level; the level of enterprises controlled by the state; and the private level. The practice of Ukraine shows that the exercising of a multilevel legal encounter during a hybrid war faces a number of problems including the intersection of actions (sometimes even direct conflict), even among authorities involved in the legal protection of state interests; and problems with collecting and analysing the information necessary to protect state interests in the legal dimension; state authorities that are not directly involved in a legal encounter may exercise actions which will complicate the legal position of the state. One of the first steps taken by the state in a hybrid conflict is, therefore, to create special authority or entrust an existing one with the coordination of the functions of lawfare. The next step of such an authority is the strategic "programming" of the opponent's legal actions with the aim of achieving an advantage in the legal dimension of a hybrid conflict.

Análise da ofensiva da seleção brasileira de futebol feminino na Copa do Mundo 2019

O presente estudo teve o objetivo de analisar as ações táticas ofensivas da seleção brasileira de futebol feminino durante a Copa do Mundo FIFA® 2019, com 103 sequencias ofensivas que compõem a amostra no decorrer da competição. Para a coleta dos dados, fez-se a observação sistemática dos jogos disponibilizados pela plataforma InStat® e gravados a partir das transmissões televisivas. Todos os dados foram modelados e analisados a partir da linguagem computacional de livre acesso Python 3.7. As variáveis de jogo analisadas foram: tempo de realização do ataque, números de contato com a bola, número de bolas recebidas/número de passes, velocidade de transmissão da bola, local de recuperação da posse de bola, forma de recuperação da posse de bola, local de conclusão da ação ofensiva e desfecho da ação ofensiva. Para análise dos dados, utilizou-se estatística descritiva e os testes de Qui-Quadrado e Kruskal-Walls (p&lt;0,05). Foram verificadas diferenças significativas apenas para as variáveis velocidade de transmissão de bola (p=0,031) e o local de recuperação de posse de bola na variável central defensiva (p=0,047). Com este estudo podemos concluir que a equipe brasileira manteve primou por interceptar as ações adversárias no último terço do campo principalmente pelo corredor esquerdo e em alguns momentos a equipe esperava as adversárias em seu campo de jogo. Também se verificou que a velocidade de transmissão da bola foi fator significante durante a fase de grupos para classificação da equipe.

Knowing Me, Knowing You: An Experiment on Mutual Payoff Information and Strategic Uncertainty

We use a laboratory experiment to study how mutual payoff information affects play in strategic settings. Subjects play the Prisoner's Dilemma or Stag Hunt game against randomly re-matched opponents under two information treatments. In our partial-information treatment subjects are shown only their own payoffs, while in our full-information treatment they are shown both their own and their opponent's payoffs. In both treatments, they receive feedback on their opponent's action after each round. We find that mutual payoff information has a substantial effect on the equilibrium reached in the Stag Hunt and convergence in both games. Using a belief-learning model and simulations of play, we provide evidence that this effect is driven not only by initial play but also by the way subjects learn. We propose that strategic uncertainty is a probable channel driving these effects.

Конфліктність соціального середовища як предмет дослідження

The article presents a theoretical and experimental substantiation of the problem of conflict of the social environment in Luhansk region as a consequence of the hybrid warfare in East of Ukraine. It is determined that the conflict is an active reciprocal actions of opponents to achieve their goals, colored by strong emotional experiences; social conflict is opened confrontation, collision of two or more subjects and participants of social interaction, the causes of which are perceived incompatible needs, interests and values. It is established that as a result of the hybrid warfare in the communities of East of Ukraine a high concentration of different categories of the population was formed, which caused an increased level of conflict in the social environment. The results of a sociological study on determining the level of conflict in the social environment in Luhansk region within the Project of EU «Intensification of the influence of teachers in Luhansk region on the processes of reconciliation and peace» are presented. It has been experimentally proven that the hybrid warfare in East of Ukraine caused a high level of conflict in the social environment of Luhansk region at the level of community, collective and individual and caused the need for targeted influence on reconciliation and peace in the region.

The impact of task load on the integration of explicit contextual priors and visual information during anticipation.

There is limited knowledge about the impact of task load on experts' integration of contextual priors and visual information during dynamic and rapidly evolving anticipation tasks. We examined how experts integrate contextual priors--specifically, prior information regarding an opponent's action tendencies--with visual information such as movement kinematics, during a soccer-specific anticipation task. Furthermore, we combined psychophysiological measures and retrospective self-reports to gain insight into the cognitive load associated with this integration. Players were required to predict the action of an oncoming opponent, with and without the explicit provision of contextual priors, under two different task loads. In addition to anticipation performance, we compared continuous electroencephalography (EEG) and self-reports of cognitive load across conditions. Our data provide tentative evidence that increased task load may impair performance by disrupting the integration of contextual priors and visual information. EEG data suggest that cognitive load may increase when contextual priors are explicitly provided, whereas self-report data suggested a decrease in cognitive load. The findings provide insight into the processing demands associated with integration of contextual priors and visual information during dynamic anticipation tasks, and have implications for the utility of priors under cognitively demanding conditions. Furthermore, our findings add to the existing literature, suggesting that continuous EEG may be a more valid measure than retrospective self-reports for in-task assessment of cognitive load.