Spatio-temporal Negotiation Protocols

Canonical problems are simplified representations of a class of real world problems. They allow researchers to compare algorithms in a standard setting which captures the most important challenges of the real world problems being modeled. In this dissertation, we focus on negotiating a collaboration in space and time, a problem with many important real world applications. Although technically a multi-issue negotiation, we show that the problem can not be represented in a satisfactory manner by previous models. We propose the Children in the Rectangular Forest (CRF) model as a possible canonical problem for negotiating spatio-temporal collaboration. In the CRF problem, two embodied agents are negotiating the synchronization of their movement for a portion of the path from their respective sources to destinations. The negotiation setting is zero initial knowledge and it happens in physical time. As equilibrium strategies are not practically possible, we are interested in strategies with bounded rationality, which achieve good performance in a wide range of practical negotiation scenarios. We design a number of negotiation protocols to allow agents to exchange their offers. The simple negotiation protocol can be enhanced by schemes in which the agents add additional information of the negotiation flow to aid the negotiation partner in offer formation. Naturally, the performance of a strategy is dependent on the strategy of the opponent and the iii characteristics of the scenario. Thus we develop a set of metrics for the negotiation scenario which formalizes our intuition of collaborative scenarios (where the agents’ interests are closely aligned) versus competitive scenarios (where the gain of the utility for one agent is paid off with a loss of utility for the other agent). Finally, we further investigate the sophisticated strategies which allow agents to learn the opponents while negotiating. We find strategies can be augmented by collaborativeness analysis: the approximate collaborativeness metric can be used to cut short the negotiation. Then, we discover an approach to model the opponent through Bayesian learning. We assume the agents do not disclose their information voluntarily: the learning needs to rely on the study of the offers exchanged during normal negotiation. At last, we explore a setting where the agents are able to perform physical action (movement) while the negotiation is ongoing. We formalize a method to represent and update the beliefs about the valuation function, the current state of negotiation and strategy of the opponent agent using a particle filter. By exploring a number of different negotiation protocols and several peer-to-peer negotiation based strategies, we claim that the CRF problem captures the main challenges of the real world problems while allows us to simplify away some of the computationally demanding but semantically marginal features of real world problems

Spatio-Temporal Context in Agent-Based Meeting Scheduling

Meeting scheduling is a common task for organizations of all sizes. It involves searching for a time and place when and where all the participants can meet. However, scheduling a meeting is generally difficult in that it attempts to satisfy the preferences of all participants. Negotiation tends to be an iterative and time consuming task. Proxy agents can handle the negotiation on behalf of the individuals without sacrificing their privacy or overlooking their preferences. This thesis examines the implications of formalizing meeting scheduling as a spatiotemporal negotiation problem. The “Children in the Rectangular Forest” (CRF) canonical model is applied to meeting scheduling. By formalizing meeting scheduling within the CRF model, a generalized problem emerges that establishes a clear relationship with other spatiotemporal distributed scheduling problems. The thesis also examines the implications of the proposed formalization to meeting scheduling negotiations. A protocol for meeting location selection is presented and evaluated using simulations

Artifical Intelligence for Human Computing

This book constitutes the thoroughly refereed post-proceedings of two events discussing AI for Human Computing: one Special Session during the Eighth International ACM Conference on Multimodal Interfaces (ICMI 2006), held in Banff, Canada, in November 2006, and a Workshop organized in conjunction with the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007), held in Hyderabad, India, in January 2007. A large number of the contributions in this state-of-the-art survey are updated and extended versions of the papers presented during these two events. In order to obtain a more complete overview of research efforts in the field of human computing, a number of additional invited contributions are also included in this book on AI for human computing. The 17 revised papers presented were carefully selected from numerous submissions to and presentations made at the two events and include invited articles to round off coverage of all relevant topics of the emerging topic. The papers are organized in three parts: a part on foundational issues of human computing, a part on sensing humans and their activities, and a part on anthropocentric interaction models

Embodied conversations: Performance and the design of a robotic dancing partner

This paper reports insights gained from an exploration of performance-based techniques to improve the design of relationships between people and responsive machines. It draws on the Emergent Objects project and specifically addresses notions of embodiment as employed in the field of performance as a means to prototype and develop a robotic agent, SpiderCrab, designed to promote expressive interaction of device and human dancer, in order to achieve ‘performative merging’. The significance of the work is to bring further knowledge of embodiment to bear on the development of human-technological interaction in general. In doing so, it draws on discursive and interpretive methods of research widely used in the field of performance but not yet obviously aligned with some orthodox paradigms and practices within design research. It also posits the design outcome as an ‘objectile’ in the sense that a continuous and potentially divergent iteration of prototypes is envisaged, rather than a singular final product. The focus on performative merging draws in notions of complexity and user experience. Keywords: Embodiment; Performance; Tacit Knowledge; Practice-As-Research; Habitus.</p