My Dear Eve... The Letters of Ernest Rutherford to Arthur Eve, 1907–1908

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Recognizing Graphs Close to Bipartite Graphs with an Application to Colouring Reconfiguration

We continue research into a well-studied family of problems that ask whether the vertices of a given graph can be partitioned into sets A and B, where A is an independent set and B induces a graph from some specified graph class G. We consider the case where G is the class of k-degenerate graphs. This problem is known to be polynomial-time solvable if k = 0 (recognition of bipartite graphs), but NP-complete if k = 1 (near-bipartite graphs) even for graphs of maximum degree 4. Yang and Yuan [DM, 2006] showed that the k = 1 case is polynomial-time solvable for graphs of maximum degree 3. This also follows from a result of Catlin and Lai [DM, 1995]. We study the general k ≥ 1 case for n-vertex graphs of maximum degree k + 2 We show how to find A and B in O(n) time for k = 1, and in O(n 2 ) time for k ≥ 2. Together, these results provide an algorithmic version of a result of Catlin [JCTB, 1979] and also provide an algorithmic version of a generalization of Brook’s Theorem, proved by Borodin, Kostochka and Toft [DM, 2000] and Matamala [JGT, 2007]. The results also enable us to solve an open problem of Feghali et al. [JGT, 2016]. For a given graph G and positive integer `, the vertex colouring reconfiguration graph of G has as its vertex set the set of `-colourings of G and contains an edge between each pair of colourings that differ on exactly on vertex. We complete the complexity classification of the problem of finding a path in the reconfiguration graph between two given `-colourings of a given graph of maximum degree k

Human Management of the Hierarchical System for the Control of Multiple Mobile Robots

In order to take advantage of autonomous robotic systems, and yet ensure successful completion of all feasible tasks, we propose a mediation hierarchy in which an operator can interact at all system levels. Robotic systems are not robust in handling un-modeled events. Reactive behaviors may be able to guide the robot back into a modeled state and to continue. Reasoning systems may simply fail. Once a system has failed it is difficult to re-start the task from the failed state. Rather, the rule base is revised, programs altered, and the task re-tried from the beginning

Sequence-learning in a self-referential closed-loop behavioural system

This thesis focuses on the problem of "autonomous agents". It is assumed that such agents want to be in a desired state which can be assessed by the agent itself when it observes the consequences of its own actions. Therefore the feedback from the motor output via the environment to the sensor input is an essential component of such a system. As a consequence an agent is defined in this thesis as a self-referential system which operates within a closed sensor- mot or-sensor feedback loop. The generic situation is that the agent is always prone to unpredictable disturbances which arrive from the outside, i.e. from its environment. These disturbances cause a deviation from the desired state (for example the organism is attacked unexpectedly or the temperature in the environment changes, ...). The simplest mechanism for managing such disturbances in an organism is to employ a reflex loop which essentially establishes reactive behaviour. Reflex loops are directly related to closed loop feedback controllers. Thus, they are robust and they do not need a built-in model of the control situation. However, reflexes have one main disadvantage, namely that they always occur "too late"; i.e., only after a (for example, unpleasant) reflex eliciting sensor event has occurred. This defines an objective problem for the organism. This thesis provides a solution to this problem which is called Isotropic Sequence Order (ISO-) learning. The problem is solved by correlating the primary reflex and a predictive sensor input: the result is that the system learns the temporal relation between the primary reflex and the earlier sensor input and creates a new predictive reflex. This (new) predictive reflex does not have the disadvantage of the primary reflex, namely of always being too late. As a consequence the agent is able to maintain its desired input-state all the time. In terms of engineering this means that ISO learning solves the inverse controller problem for the reflex, which is mathematically proven in this thesis. Summarising, this means that the organism starts as a reactive system and learning turns the system into a pro-active system. It will be demonstrated by a real robot experiment that ISO learning can successfully learn to solve the classical obstacle avoidance task without external intervention (like rewards). In this experiment the robot has to correlate a reflex (retraction after collision) with signals of range finders (turn before the collision). After successful learning the robot generates a turning reaction before it bumps into an obstacle. Additionally it will be shown that the learning goal of "reflex avoidance" can also, paradoxically, be used to solve an attraction task

The Wooster Voice (Wooster, OH), 1984-01-20

This edition of the College of Wooster student run newspaper was published on January 20 of 1984 and it is twelve pages long. Study Of 1982 Wooster Grads Proves Impressive, a report associated the College of Wooster education with favorable prospects for jobs or postgraduate studies. SAB Winter Olympics To Begin, the Recreation Committee presents the 1984 Wooster Winter Olympics. New Orleans Jazz Group To Perform, the Louisiana Repertory Jazz Ensemble to perform at Lowry. Athletic updates for the past week are highlighted on page nine. An advertisement for a spring break trip encompasses the final page.https://openworks.wooster.edu/voice1981-1990/1074/thumbnail.jp

Catalogue of Saint Ignatius College, Cleveland, Ohio. 1918-1919

Catalogue of Saint Ignatius College, Cleveland, Ohio 1918-1919https://collected.jcu.edu/stignatiuscatalogues/1032/thumbnail.jp