Using Punch and Judy as a story domain, we describe an interactive puppet show, where the flow and content of the story can be influenced by the actions of the audience. As the puppet show is acted out, the audience reacts to events by cheering or booing the characters. This changes the emotional state of each agent, potentially causing them to change their actions, altering the course of the n...

To Whom, When, and How Much to Discount? A Constrained Optimization of Customized Temporal Discounts Joseph Johnson a,∗, Gerard J. Tellis b,1, Edward H. Ip c,2 a University of Miami, United States b Marshal School of Business, University of Southern California, United States c Wake Forest University School of Medicine, 3rd Floor MRI Building Medical Center Boulevard, Winston-Salem, NC 27103, Un...

and Applied Analysis 3 2.3. The Improved Accepted Condition for d k . Borrowed from the usual trust region idea, we also need to define the following predicted reduction for the violation function h(x) = ‖c(x)‖ 2 predc k = h (x k ) − 󵄩󵄩󵄩󵄩 c k + A T

Precedence constrained sequencing problem (PCSP) is related to locate the optimal sequence with the shortest traveling time among all feasible sequences. In PCSP, precedence relations determine sequence of traveling between any two nodes. Various methods and algorithms for effectively solving the PCSP have been suggested. In this paper we propose a cuckoo search algorithm (CSA) for effectively ...

This paper presents an experimental investigation of the Sounds of Silence (SoS) harmony search metaheuristic for the multi-mode resource-constrained project scheduling problem (MRCPSP) using a pre-optimized starting repertoire. The presented algorithm is based on the time oriented version of the SoS harmony search metaheuristic developed by Csébfalvi et al. [1] for the single-mode resource-con...

Constrained optimization problems have a wide range of applications in science, economics, and engineering. In this paper, a neural network model is proposed to solve a class of nonsmooth constrained optimization problems with a nonsmooth convex objective function subject to nonlinear inequality and affine equality constraints. It is a one-layer non-penalty recurrent neural network based on the...

Abstract Statistical clustering criteria with free scale parameters and unknown cluster sizes are inclined to create small, spurious clusters. To mitigate this tendency a statistical model for cardinality–constrained clustering of data with gross outliers is established, its maximum likelihood and maximum a posteriori clustering criteria are derived, and their consistency and robustness are ana...