Hippocampal predictive maps of an uncertain world

Humans and other animals can solve a wide variety of decision-making problems with remarkable flexibility. This flexibility is thought to derive from an internal model of the world, or ‘cognitive map’, used to predict the future and plan actions accordingly. A recent theoretical proposal suggests that the hippocampus houses a representation of long-run state expectancies. These “successor representations” (SRs) occupy a middle ground between model-free and model-based reinforcement learning strategies. However, it is not clear whether SRs can explain hippocampal contributions to spatial and model-based behaviour, nor how a putative hippocampal SR might interface with striatal learning mechanisms. More generally, it is not clear how the predictive map should encode uncertainty, and how an uncertainty-augmented predictive map modifies our experimental predictions for animal behaviour. In the first part of this thesis, I investigated whether viewing the hippocampus as an SR can explain experiments contrasting hippocampal and dorsolateral striatal contributions to behaviour in spatial and non-spatial tasks. To do this, I modelled the hippocampus as an SR and DLS as model-free reinforcement learning, combining their outputs via their relative reliability as a proxy for uncertainty. Current SR models do not formally address uncertainty. Therefore I extended the learning of SRs by temporal differences to include managing uncertainty in new observations versus existing knowledge. I generalise this approach to a multi-task setting using a Bayesian nonparametric switching Kalman Filter, allowing the model to learn and maintain multiple task-specific SR maps and infer which one to use at any moment based on the observations. I show that this Bayesian SR model captures animal behaviour in tasks which require contextual memory and generalisation. In conclusion, I consider how the hippocampal contribution to behaviour can be considered as a predictive map when adapted to take account of uncertainty and combined with other behavioural controllers

System analysis and design of a low-cost micromechanical seeker system

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.Includes bibliographical references (p. 137-140).Precision guided targeting systems have been in use by the U.S. military for the last half-century. The desire for high targeting accuracies while maintaining minimal collateral damage has driven the implementation of guidance systems on a myriad of different platforms. Current seeker systems using global positioning system (GPS)-aided technology offer good accuracy, but are limited by an adversary's signal jamming capabilities and the dynamic nature of the military target environment. Furthermore, ultra-accurate inertial measurement units (IMU) that serve as stand-alone guidance systems are very expensive and offer no terminal guidance enhancement. As a result, it is cost prohibitive to equip some platforms with precision guidance capability. The demand for high accuracy at low cost has prompted substantial recent development of micro-electromechanical systems (MEMS) IMU's and optical focal plane arrays (FPA). The resulting decreasing device size and production costs coupled with higher unit performance have created opportunities for implementing seeker-enabled systems on platforms previously deemed impractical. As a result, the author proposes a design methodology to develop a low-cost system while satisfying stringent performance requirements. The methodology is developed within the context of a strap-down seeker system for tactical applications. The design tenets of the optical sensor, the inertial sensor, and projectile flight dynamics were analyzed in-depth for the specific scenario. The results of each analysis were combined to formulate a proposed system.(cont.) The system was then modeled to produce system miss distance estimates for differing engagement situations. The system demonstrated 3[sigma] miss distance estimates that were less than the maximum allowable error in each case. The system cost was tabulated and a production price was approximated. Using current technology and pricing information for the main components, the analysis shows that a system with a 3[sigma] miss distance of 0.801 m could be built for a unit price in the range of $11,730 -$19,550, depending on production costs. Design limitations are discussed, as well as strategies to improve the analysis for future consideration.by Brian J. Nagle.S.M

The Telecommunications and Data Acquisition Report

This publication, one of a series formerly titled The Deep Space Network Progress Report, documents DSN progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported

Formation-Based Odour Source Localisation Using Distributed Terrestrial and Marine Robotic Systems

This thesis tackles the problem of robotic odour source localisation, that is, the use of robots to find the source of a chemical release. As the odour travels away from the source, in the form of a plume carried by the wind or current, small scale turbulence causes it to separate into intermittent patches, suppressing any gradients and making this a particularly challenging search problem. We focus on distributed strategies for odour plume tracing in the air and in the water and look primarily at 2D scenarios, although novel results are also presented for 3D tracing. The common thread to our work is the use of multiple robots in formation, each outfitted with odour and flow sensing devices. By having more than one robot, we can gather observations at different locations, thus helping overcome the difficulties posed by the patchiness of the odour concentration. The flow (wind or current) direction is used to orient the formation and move the robots up-flow, while the measured concentrations are used to centre the robots in the plume and scale the formation to trace its limits. We propose two formation keeping methods. For terrestrial and surface robots equipped with relative or absolute positioning capabilities, we employ a graph-based formation controller using the well-known principle of Laplacian feedback. For underwater vehicles lacking such capabilities, we introduce an original controller for a leader-follower triangular formation using acoustic modems with ranging capabilities. The methods we propose underwent extensive experimental evaluation in high-fidelity simulations and real-world trials. The marine formation controller was implemented in MEDUSA autonomous vehicles and found to maintain a stable formation despite the multi-second ranging period. The airborne plume tracing algorithm was tested using compact Khepera robots in a wind tunnel, yielding low distance overheads and reduced tracing error. A combined approach for marine plume tracing was evaluated in simulation with promising results