In the debate between simple inference heuristics and complex decision mechanisms, we take a position squarely in the middle. A decision making process that extends to both naturalistic and novel settings should extend beyond the confines of this debate; both simple heuristics and complex mechanisms are cognitive skills adapted to and appropriate for some circumstances but not for others. Rather than ask `Which skill is better?'' it is often more important to ask `When is a skill justified?'' The selection and (...) application of an appropriate cognitive skill for a particular problem has both costs and benefits, and therefore requires the resolution of a tradeoff. In revisiting satisficing, we observe that the essence of satisficing is tradeoff. Unlike heuristics, which derive their justification from empirical phenomena, and unlike optimal solutions, which derive their justification by an evaluation of alternatives, satisficing decision-making derives its justification by an evaluation of consequences. We formulate and present a satisficing decision paradigm that has its motivation in Herbert Simon''s work on bounded rationality. We characterize satisficing using a cost–benefit tradeoff, and generate a decision rule applicable to both designing intelligent machines as well as describing human behavior. (shrink)

Wilderness Search and Rescue is the process of finding and assisting persons who are lost in remote wilderness areas. Because such areas are often rugged or relatively inaccessible, searching for missing persons can take huge amounts of time and resources. Camera-equipped mini-Unmanned Aerial Vehicles have the potential for speeding up the search process by enabling searchers to view aerial video of an area of interest while closely coordinating with nearby ground searchers. In this paper, we report on lessons learned by (...) trying to use UAVs to support WiSAR. Our research methodology has relied heavily on field trials involving searches conducted under the direction of practicing search and rescue personnel but using simulated missing persons. Lessons from these field trials include the immediate importance of seeing things well in the video, the field need for defining and supporting various roles in the search team, role-specific needs like supporting systematic search by providing a visualization tool to represent the quality of the search, and the on-going need to better support interactions between ground and video searchers. Surprisingly to us, sophisticated autonomous search patterns were less critical than we anticipated, though advances in video enhancement and visualizing search progress, as well as ongoing work to model the likely location of a missing person, open up the possibility of closing the loop between UAV path-planning, search quality, and the likely location of a moving missing person. Keywords: Unmanned Aerial Vehicles, Wilderness Search and Rescue, Human–Robot Interaction, Human Factors, Field Robotics, Graphical User Interfaces. (shrink)