Bid Decision Making with Prospect Game Theory

Author(s):  
Min-Yuan Cheng ◽  
Chia-Chi Hsiang
Keyword(s):  
Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shion Maeda ◽  
Nicolas Chauvet ◽  
Hayato Saigo ◽  
Hirokazu Hori ◽  
Guillaume Bachelier ◽  
...  

AbstractCollective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.


2014 ◽  
Vol 986-987 ◽  
pp. 400-403 ◽  
Author(s):  
Kuan Lu ◽  
Wen Shan Gao ◽  
Jing Li ◽  
Wan Lei Xue ◽  
Wen Xue Sun

First, behavior models of the station operator and consumer are established considering all the main factors. Second, an optimized EV charging pricing method using Game Theory is introduced based on benefit-cost analysis. The calculation of government subsidies is also proposed in order to reach an equilibrium charging price. Finally, actual data of Hebei is used and results are shown to give supports to local government and charging station operator’s decision making.


Author(s):  
Yu-Chung Chang ◽  

Based on the perspective of the quantum game, this paper explores when the online direct sales channel takes the free-riding behavior after the retail channel provides high-quality experience and services and how the dual-channel supply chain establishes a commodity pricing strategy. The retailer’s selling price follows a decreasing function of the free-riding behavior coefficient. while the online direct selling price does an increasing function of the free-riding behavior coefficient. Under centralized decision-making, there is no quantum entanglement, so the quantum game solution is consistent with the classical game solution. Under decentralized decision-making, the optimal price and profit of the quantum game are higher than those of the classical game when the quantum entanglement degree is greater than zero. When the quantum entanglement tends to be infinite, the optimal price of the quantum game finally remains in convergence. The quantum game theory is a more optimal decision-making method than the classical game theory.


Author(s):  
Ayan Sinha ◽  
Farrokh Mistree ◽  
Janet K. Allen

The effectiveness of the use of game theory in addressing multi-objective design problems has been illustrated. For the most part, researchers have focused on design problems at single level. In this paper, we illustrate the efficacy of using game theoretic protocols to model the relationship between multidisciplinary engineering teams and facilitate decision making at multiple levels. We will illustrate the protocols in the context of an underwater vehicle with three levels that span material and geometric modeling associated with microstructure mediated design of the material and vehicle.


2018 ◽  
Vol 8 (12) ◽  
pp. 2530
Author(s):  
Nan Nie ◽  
Xin Zhang ◽  
Chu Fang ◽  
Qiu Zhu ◽  
Jiao Lu ◽  
...  

Game theory—the scientific study of interactive, rational decision making—describes the interaction of two or more players from macroscopic organisms to microscopic cellular and subcellular levels. Life based on molecules is the highest and most complex expression of molecular interactions. However, using simple molecules to expand game theory for molecular decision-making remains challenging. Herein, we demonstrate a proof-of-concept molecular game-theoretical system (molecular prisoner’s dilemma) that relies on formation of the thymine–Hg2+–thymine hairpin structure specifically induced by Hg2+ and fluorescence quenching and molecular adsorption capacities of cobalt oxyhydroxide (CoOOH) nanosheets, resulting in fluorescence intensity and distribution change of polythymine oligonucleotide 33-repeat thymines (T33). The “bait” molecule, T33, interacted with two molecular players, CoOOH and Hg2+, in different states (absence = silence and presence = betrayal), regarded as strategies. We created conflicts (sharing or self-interest) of fluorescence distribution of T33, quantifiable in a 2 × 2 payoff matrix. In addition, the molecular game-theoretical-system based on T33 and CoOOH was used for sensing Hg2+ over the range of 20 to 600 nM with the detection limit of 7.94 nM (3σ) and for determination of Hg2+ in pond water. Inspired by the proof-of-concept for molecular game theory, various molecular decision-making systems could be developed, which would help promote molecular information processing and generating novel molecular intelligent decision systems for environmental monitoring and molecular diagnosis and therapy.


2018 ◽  
Vol 19 (1) ◽  
pp. 154-175 ◽  
Author(s):  
Animesh DEBNATH ◽  
Abhirup BANDYOPADHYAY ◽  
Jagannath ROY ◽  
Samarjit KAR

The long-term evolution of multi agent multi criteria decision making (MCDM) and to obtain sustainable decision a novel methodology is proposed based on evolutionary game theory. In this paper multi agent MCDM is represented as an evolutionary game and the evolutionary strategies are defined as sustainable decisions. Here we consider the problem of decision making in Indian Tea Industry. The agents in this game are essentially Indian Tea Estate owner and Indian Tea board. The replicator dynamics of the evolutionary game are studied to obtain evolutionary strategies which could be defined as sustainable strategies. The multi agent MCDM in Indian Tea Industry is considered under different socio-political and Corporate Social Responsibility scenario and groups of Indian Tea Industry. Again, the impacts of imprecision and market volatility on the outcome of some strategies (decisions) are studied. In this paper the imprecision on the impact of the strategies are modelled as fuzzy numbers whereas the market volatility is taken into account as white noise. Hence the MCDM problem for Indian Tea Industry is modelled as a hybrid evolutionary game. The probabilities of strategies are obtained by solving hybrid evolutionary game and could be represented as a Dempster-Shafer belief structure. The simulation results facilitate the Decision Makers to choose the strategies (decisions) under different type of uncertainty.


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