Emerging Artificial Societies Through Learning

The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.Artificial Societies, Evolution of Language, Decision Trees, Peer-To-Peer Networks, Social Learning

Impact of nationwide enhanced implementation of best practices in pancreatic cancer care (PACAP-1): A multicenter stepped-wedge cluster randomized controlled trial

Background: Pancreatic cancer has a very poor prognosis. Best practices for the use of chemotherapy, enzyme replacement therapy, and biliary drainage have been identified but their implementation in daily clinical practice is often suboptimal. We hypothesized that a nationwide program to enhance implementation of these best practices in pancreatic cancer care would improve survival and quality of life. Methods/design: PACAP-1 is a nationwide multicenter stepped-wedge cluster randomized controlled superiority trial. In a per-center stepwise and randomized manner, best practices in pancreatic cancer care regarding the use of (neo)adjuvant and palliative chemotherapy, pancreatic enzyme replacement therapy, and metal biliary stents are implemented in all 17 Dutch pancreatic centers and their regional referral networks during a 6-week initiation period. Per pancreatic center, one multidisciplinary team functions as reference for the other centers in the network. Key best practices were identified from the literature, 3 years of data from existing nationwide registries within the Dutch Pancreatic Cancer Project (PACAP), and national expert meetings. The best practices follow the Dutch guideline on pancreatic cancer and the current state of the literature, and can be executed within daily clinical practice. The implementation process includes monitoring, return visits, and provider feedback in combination with education and reminders. Patient outcomes and compliance are monitored within the PACAP registries. Primary outcome is 1-year overall survival (for all disease stages). Secondary outcomes include quality of life, 3- and 5-year overall survival, and guideline compliance. An improvement of 10% in 1-year overall survival is considered clinically relevant. A 25-month study duration was chosen, which provides 80% statistical power for a mortality reduction of 10.0% in the 17 pancreatic cancer centers, with a required sample size of 2142 patients, corresponding to a 6.6% mortality reduction and 4769 patients nationwide. Discussion: The PACAP-1 trial is designed to evaluate whether a nationwide program for enhanced implementation of best practices in pancreatic cancer care can improve 1-year overall survival and quality of life. Trial registration: ClinicalTrials.gov, NCT03513705. Trial opened for accrual on 22th May 2018

Modeling Organizational Change for Naval Missions MARK HOOGENDOORN 1

Abstract. The naval domain is characterized by a dynamic environment. This requires constant adaptation of the organization, choosing between a wide variety of options. The consequences of the different options are difficult to foresee and hence, it is hard to judge which option is best. This paper presents automated support for the simulation, visualization, and validation of such adaptive multi-agent organisations. Generic simulation properties are specified using a formal modeling approach. Furthermore, results of a realistic case study are presented, and validated by means of properties obtained from naval experts. Finally, a tool is introduced that enables an insightful visualization of the simulation results

Computational Modeling of Organization in Honeybee Societies Based on Adaptive Role Allocation

Abstract. One of the unique features of the organization in honeybee societies is the ability to adapt to environmental circumstances in a highly decentralized way. This adaptation takes the form of changes in the allocation of bees to roles, whereby bees individually decide to take up certain roles that require attention. Within the domain of computational modeling of multi-agent systems a trend has developed to model such systems from an organizational perspective. Usually this is done by describing multi-agent systems as organizations using structural elements such as roles and groups, and behavioral properties of these elements: for example, expressions for role behavior, specifying how agents should behave once they fulfill a certain role. In dynamic environments, changes in environmental circumstances may require changes in such organizations as well. In this paper, the change process as seen in honeybee colonies has been modeled by means of techniques from the domain of multi-agent organizations. This results in an adaptive multi-agent organizational model that is able to cope with changing environmental circumstances. 1

Computational modeling of organization in honey bee societies based on adaptive role allocation

One of the unique features of the organization in honey bee societies is the ability to adapt to environmental circumstances in a highly decentralized way. This adaptation takes the form of changes in the allocation of bees to roles, whereby bees individually decide to take up certain roles that require attention. Within the domain of computational modeling of multiagent systems, a trend has developed to model such systems from an organizational perspective. Usually this is done by describing multiagent systems as organizations using structural elements such as roles and groups and behavioral properties of these elements, for example, expressions for role behavior, specifying how agents should behave once they fulfill a certain role. In dynamic environments, changes in environmental circumstances may require changes in such organizations as well. In this chapter, the change process as seen in honey bee colonies has been modeled by means of techniques from the domain of multiagent organizations. This results in an adaptive multiagent organizational model that is able to cope with changing environmental circumstances

CHAPTER # FORMAL ANALYSIS OF DYNAMICS WITHIN PHILOSOPHY OF MIND BY COMPUTER SIMULATION

Abstract. Computer simulations can be useful tools to support philosophers in validating their theories, especially when these theories concern phenomena showing nontrivial dynamics. Such theories are usually informal, whilst for computer simulation a formally described model is needed. In this paper, a methodology is proposed to gradually formalise philosophical theories in terms of logically formalised dynamic properties. One outcome of this process is an executable logic-based temporal specification, which within a dedicated software environment can be used as a simulation model to perform simulations. This specification provides a logical formalisation at the lowest aggregation level of the basic mechanisms underlying a process. In addition, dynamic properties at a higher aggregation level that may emerge from the mechanisms specified by the lower level properties, can be specified. Software tools are available to support specification, and to automatically check such higher level properties against the lower level properties and against generated simulation traces. As an illustration, three case studies are discussed showing successful applications of the approach to formalise and analyse, among others, Clark’s theory on extended mind, Damasio’s theory on core consciousness, and Dennett’s perspective on intertemporal decision making and altruism. 1