Intelligent tutoring agent for settlers of Catan

An Intelligent Tutoring Agent (ITA) for the board game Settlers of Catan (SoC) is introduced. It uses CLIPS knowledge bases, connected by JCLIPS to a JAVA implementation of SoC. It is founded on a new theoretical framework that describes the development of negotiation skills in children. Using this framework, the ITA helps children in developing negotiation skills through play, which makes it unique in its kind

Revealing Resources in Strategic Contexts

International audienceIdentifying an optimal game strategy often involves estimating the strategies of other agents, which in turn depends on hidden parts of the game state. In this paper we focus on the win-lose game The Settlers of Catan (or Settlers ), in which players negotiate over limited resources. More precisely, our goal is to map each player’s utterances in such negotiations to a model of which resources they currently possess,or don’t possess. Our approach comprises three subtasks: (a) identify whether a given utterance (dialogue turn) reveals possession of a resource, or not; (b) determine the type of resource; and (c) determine the exact interval representing the quantity involved. This information can be exploited by a Settlers playing agent to identify his optimal strategy for winning

Strategic dialogue management via deep reinforcement learning

Artificially intelligent agents equipped with strategic skills that can negotiate during their interactions with other natural or artificial agents are still underdeveloped. This paper describes a successful application of Deep Reinforcement Learning (DRL) for training intelligent agents with strategic conversational skills, in a situated dialogue setting. Previous studies have modelled the behaviour of strategic agents using supervised learning and traditional reinforcement learning techniques, the latter using tabular representations or learning with linear function approximation. In this study, we apply DRL with a high-dimensional state space to the strategic board game of Settlers of Catan---where players can offer resources in exchange for others and they can also reply to offers made by other players. Our experimental results report that the DRL-based learnt policies significantly outperformed several baselines including random, rule-based, and supervised-based behaviours. The DRL-based policy has a 53% win rate versus 3 automated players (`bots'), whereas a supervised player trained on a dialogue corpus in this setting achieved only 27%, versus the same 3 bots. This result supports the claim that DRL is a promising framework for training dialogue systems, and strategic agents with negotiation abilities

Game-Based Learning in Counselor Education: Strategies for Counselor Training

Counselors value equity, diversity, and inclusion (American Counseling Association, 2018). Counselor educators are tasked with ensuring counselor trainees are competent in empathetic understanding, cultural awareness, and advocacy. Game-based learning is a teaching strategy that promotes the process of acquiring empathy, cultural awareness, and advocacy (Cheng & Su, 2012; Qian & Clark, 2016). Game-based learning has many documented benefits over the last two decades (Hwang & Wu, 2012; Tsai et al., 2011) yet counselor education has not incorporated it into counselor training. The authors addressed this gap by providing a conceptual framework for incorporating GBL into training with implications for counselor educators and counselor trainees

Game-Based Learning in Counselor Education: Strategies for Counselor Training

Counselors value equity, diversity, and inclusion (American Counseling Association, 2018). Counselor educators are tasked with ensuring counselor trainees are competent in empathetic understanding, cultural awareness, and advocacy. Game-based learning is a teaching strategy that promotes the process of acquiring empathy, cultural awareness, and advocacy (Cheng & Su, 2012; Qian & Clark, 2016). Game-based learning has many documented benefits over the last two decades (Hwang & Wu, 2012; Tsai et al., 2011) yet counselor education has not incorporated it into counselor training. The authors addressed this gap by providing a conceptual framework for incorporating GBL into training with implications for counselor educators and counselor trainees

Game-Based Learning in Counselor Education: Strategies for Counselor Training

Counselors value equity, diversity, and inclusion (American Counseling Association, 2018). Counselor educators are tasked with ensuring counselor trainees are competent in empathetic understanding, cultural awareness, and advocacy. Game-based learning is a teaching strategy that promotes the process of acquiring empathy, cultural awareness, and advocacy (Cheng & Su, 2012; Qian & Clark, 2016). Game-based learning has many documented benefits over the last two decades (Hwang & Wu, 2012; Tsai et al., 2011) yet counselor education has not incorporated it into counselor training. The authors addressed this gap by providing a conceptual framework for incorporating GBL into training with implications for counselor educators and counselor trainees

The Settlers of Catan and a Study of Trade in Non-cooperative Games

Free trade has long been hailed as the world’s answer to increased competitiveness, greater overall wealth and a higher standard of living. Adam Smith’s ideas on the foundations of capitalism assert that open market policies lead to global economic growth, and conversely that protectionist measures stunt growth and inflate prices. Critics argue that protectionism helps protect developing markets and industries and prevents unfair competition. But in the debate over trade which economic policy is actually best? To answer this question I conducted an experiment using the board game, The Settlers of Catan, as an economic model. I isolated trade as a variable and looked at what effect the frequency and magnitude of trade had on resource and point accumulation within the game. I collected data for 10 games where trade was allowed and 10 games where it was forbidden, attempting to identify an empirical contrast between the two versions. What I found is that no-trade games consistently out produced free-trade games in terms of both point and resource accumulation, and that there was no correlation between trade and either total points or total resources. I also found that despite being given the option to trade, players would frequently reject seemingly fair offers and instead pay a higher price for resources through the in-game bank. I reasoned that this behavior was a result of players trying to maintain or extend their competitive advantage, which they were able to do by maximizing their utility, or value gained, for the game as a whole rather than at any one specific stage in the game. This explains why trading was so rare and why no-trade games outperformed full-trade games in the experiment. The significance of this result can be especially felt in the labor market, where labor is a resource traded by workers to their employers. I use the recent NFL and NBA lockouts as case studies to show how utility maximization behavior can be applied to real world economic situations