Learning and Communication in Sender-Reciever Games: An Economic Investigation

This paper compares the performance of stimulus response (SR) and belief-based learning (BBL) using data from game theory experiments. The environment, extensive form games played in a population setting, is novel in the empirical literature on learning in games. Both the SR and BBL models fit the data reasonably well in common interest games with history while the test results accept SR and reject BBL in games with no history and in all but one of the divergent interest games. Estimation is challenging since the likelihood function is not globally concave and the results may be subject to convergence bias.econometrics;game theory and experiments

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping

Learning and Communication in Sender-Reciever Games:An Economic Investigation

This paper compares the performance of stimulus response (SR) and belief-based learning (BBL) using data from game theory experiments. The environment, extensive form games played in a population setting, is novel in the empirical literature on learning in games. Both the SR and BBL models fit the data reasonably well in common interest games with history while the test results accept SR and reject BBL in games with no history and in all but one of the divergent interest games. Estimation is challenging since the likelihood function is not globally concave and the results may be subject to convergence bias.

Modelling Behavioural Diversity for Learning in Open-Ended Games

Promoting behavioural diversity is critical for solving games with non-transitive dynamics where strategic cycles exist, and there is no consistent winner (e.g., Rock-Paper-Scissors). Yet, there is a lack of rigorous treatment for defining diversity and constructing diversity-aware learning dynamics. In this work, we offer a geometric interpretation of behavioural diversity in games and introduce a novel diversity metric based on determinantal point processes (DPP). By incorporating the diversity metric into best-response dynamics, we develop diverse fictitious play and diverse policy-space response oracle for solving normal-form games and open-ended games. We prove the uniqueness of the diverse best response and the convergence of our algorithms on two-player games. Importantly, we show that maximising the DPP-based diversity metric guarantees to enlarge the gamescape -- convex polytopes spanned by agents' mixtures of strategies. To validate our diversity-aware solvers, we test on tens of games that show strong non-transitivity. Results suggest that our methods achieve at least the same, and in most games, lower exploitability than PSRO solvers by finding effective and diverse strategies.Comment: corresponds to <[email protected]

An iterative semi-implicit scheme with robust damping

An efficient, iterative semi-implicit (SI) numerical method for the time integration of stiff wave systems is presented. Physics-based assumptions are used to derive a convergent iterative formulation of the SI scheme which enables the monitoring and control of the error introduced by the SI operator. This iteration essentially turns a semi-implicit method into a fully implicit method. Accuracy, rather than stability, determines the timestep. The scheme is second-order accurate and shown to be equivalent to a simple preconditioning method. We show how the diffusion operators can be handled so as to yield the property of robust damping, i.e., dissipating the solution at all values of the parameter \mathcal D\dt, where $\mathcal D$ is a diffusion operator and \dt the timestep. The overall scheme remains second-order accurate even if the advection and diffusion operators do not commute. In the limit of no physical dissipation, and for a linear test wave problem, the method is shown to be symplectic. The method is tested on the problem of Kinetic Alfv\'en wave mediated magnetic reconnection. A Fourier (pseudo-spectral) representation is used. A 2-field gyrofluid model is used and an efficacious k-space SI operator for this problem is demonstrated. CPU speed-up factors over a CFL-limited explicit algorithm ranging from $\sim20$ to several hundreds are obtained, while accurately capturing the results of an explicit integration. Possible extension of these results to a real-space (grid) discretization is discussed.Comment: Submitted to the Journal of Computational Physics. Clarifications and caveats in response to referees, numerical demonstration of convergence rate, generalized symplectic proo

A perturbative approach to multireference equation-of-motion coupled cluster

We introduce a variant of the multireference equation-of-motion coupled-cluster (MR-EOMCC) method where the amplitudes used for the similarity transformations are estimated from perturbation theory. Consequently, the new variant retains the many-body formalism, a reliance on at most two-body densities, and the state-universal character. As a non-iterative variant, computational costs are reduced, and no convergence difficulties with near-singular amplitudes can arise. Its performance was evaluated on several test sets covering transition metal atoms, small diatomics, and organic molecules against (near-)full CI quality reference data. We further highlight its efficacy on the weakly avoided crossing of LiF and place MR-EOMCC and the new variant into context with linear response theory. The accuracy of the variant was found to be at least on par with expectations for multireference perturbation theories, judging by the NEVPT2 method. The variant can be especially useful in multistate situations where the high accuracy of the iterative MR-EOMCC method is not required

Dropped object impact analysis on subsea pipelines

This thesis studies the response of a subsea pipeline's structure when a dropped object hits it. The pipeline and seabed were modelled using solid elements, while the container model was imported from Aker Solutions and is composed of shell elements. LS-DYNA, a finite element software, was used to conduct the analysis. The key parameters studied in this research were impact force, internal energy, and pipeline deformation. Thirteen different cases have been analysed in addition to three cases used in a mesh convergence test. The impact scenarios have been described in Table 8, Chapter 4.11 and the three mesh convergence cases have been described in Table 9, Chapter 4.11. The thesis includes a literature study of relevant standards and previous research that has been conducted. DNVGL-RP-C204 and DNVGL-RP-F107 are the applicable standards for dropped objects in this thesis. DNVGL-RP-C204 provides essential information on calculating impact velocity, dissipation of strain energy, and force-deformation curve for tubular members. At the same time, DNVGL-RP-F107 presents information on drop probability in crane lifting operations, the hit probability onto a subsea pipeline, and various protection methods available in the industry. A mesh convergence study was carried out to determine the optimal mesh size for the models. This involved comparing three models with the same properties, apart from the mesh size, and observing at which mesh size the outcome converged. The objective was to identify the largest feasible mesh size that would have little to no impact on the precision of the results. A comprehensive parametric study of the subsea pipeline was conducted to analyse its response to the different cases. This involved testing for various scenarios on the pipeline under different conditions, such as altering the soil parameters, protection method, yield strength, and the impact angle of the container. The container's velocity was kept constant at 10 m/s in all the impact scenarios. The impact angle was identified as a crucial factor in the extent of damage inflicted on the pipeline. The use of concrete coating reduced the deformation and the internal energy in the pipeline. With a flexible seabed, the internal energy was reduced for the scenario with coating. However, that was not the case for the unprotected pipeline. The possible reason is explained in this thesis. By increasing the pipeline’s yield strength, the internal energy and deformation of the pipeline were significantly reduced

Stochastic user equilibrium assignment with traffic-responsive signal control

This paper considers the Stochastic User Equilibrium (SUE) assignment problem for a signal-controlled network in which intersection control is flow-responsive. The problem is addressed within a Combined Traffic Assignment and Control (CTAC) modeling framework, in which the calculation of user equilibrium link flows is integrated with the calculation of consistent signal settings [1]. It is assumed that network equilibrium is dispersed due to user misperceptions of travel times, and that the intersection control system is designed to allow the persistent adjustment of signal settings in response to traffic flow variations. Thus, the model simulates real- world situations in which network users have limited information and signal control is traffic-actuated. The SUE- based CTAC model is solved algorithmically by means of the so- called Iterative Optimization and Assignment (IOA) procedure, a widely used heuristic which relies on the alternate execution of a control step (signal setting calculation for fixed link flows) and an assignment step (network equilibration under fixed signal settings). The main objective of the study is to define a methodological framework for the evaluation of the performance of various traffic-responsive signal control strategies in interaction with different levels of user information, as represented by the spread parameter of the perceived travel time distribution assumed in the SUE assignment submodel. The results are of practical relevance in a policy context, as they provide a basis for assessing the potential integration of Advanced Traveler Information Systems (ATIS) and signal control systems. Several computational experiments are carried out on a small, contrived network and using realistic intersection delay functions, in order to test the behavior of the model under a wide range of conditions; in particular, convergence pattern and network performance measures at equilibrium are analyzed under alternative information/control scenarios and for various demand levels. The issue of uniqueness of the model solution is addressed as well. Reference: [1] Meneguzzer C. (1997). Review of models combining traffic assignment and signal control. ASCE Journal of Transportation Engineering, vol. 123, no. 2, pp. 148-155.