Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization

Artificial autonomous agents and robots interacting in complex environments are required to continually acquire and fine-tune knowledge over sustained periods of time. The ability to learn from continuous streams of information is referred to as lifelong learning and represents a long-standing challenge for neural network models due to catastrophic forgetting. Computational models of lifelong learning typically alleviate catastrophic forgetting in experimental scenarios with given datasets of static images and limited complexity, thereby differing significantly from the conditions artificial agents are exposed to. In more natural settings, sequential information may become progressively available over time and access to previous experience may be restricted. In this paper, we propose a dual-memory self-organizing architecture for lifelong learning scenarios. The architecture comprises two growing recurrent networks with the complementary tasks of learning object instances (episodic memory) and categories (semantic memory). Both growing networks can expand in response to novel sensory experience: the episodic memory learns fine-grained spatiotemporal representations of object instances in an unsupervised fashion while the semantic memory uses task-relevant signals to regulate structural plasticity levels and develop more compact representations from episodic experience. For the consolidation of knowledge in the absence of external sensory input, the episodic memory periodically replays trajectories of neural reactivations. We evaluate the proposed model on the CORe50 benchmark dataset for continuous object recognition, showing that we significantly outperform current methods of lifelong learning in three different incremental learning scenario

Incremental QBF Solving

We consider the problem of incrementally solving a sequence of quantified Boolean formulae (QBF). Incremental solving aims at using information learned from one formula in the process of solving the next formulae in the sequence. Based on a general overview of the problem and related challenges, we present an approach to incremental QBF solving which is application-independent and hence applicable to QBF encodings of arbitrary problems. We implemented this approach in our incremental search-based QBF solver DepQBF and report on implementation details. Experimental results illustrate the potential benefits of incremental solving in QBF-based workflows.Comment: revision (camera-ready, to appear in the proceedings of CP 2014, LNCS, Springer

ADR-based Workplace Conflict Management Systems: A Case of American Exceptionalism

[Excerpt] The diffusion of ADR-based conflict management systems is a development increasingly highlighted in the literature. Organizations are seen as putting in place multiple procedures and practices so that different varieties of workplace conflict can be effectively addressed. Just why organizations are electing to introduce these integrated bundles of innovative conflict management practices is a matter of debate, but many view the development as transforming the manner in which workplace problems are managed in modern organizations, with some even pronouncing that it amounts to the rewriting of the social contract at work (Lipsky and Seeber 2006). This paper argues that to the extent to which conflict management systems are being diffused, it is occurring mainly in the USA became the institutional context for the management of the employment relationship creates considerable incentives for the adoption of ADR-inspired conflict management innovations. Other Anglo-American countries, where it might be thought reasonable to expect a similar pattern of ADR innovation at the workplace to emerge, are not experiencing any discernible shift towards conflict management systems inside organizations. It is suggested that in the absence of institutional incentives to adopt workplace management systems, organizations are unlikely to opt for radical conflict management innovations. At the same time, drawing on research in the Irish context, it is argued that tried-and-tested conflict management practices do change over time, with an incremental and evolutionary approach adopted by some organizations to upgrade practices considered the most interesting development. The paper is organized as follows. The first section assesses why the emergence of integrated conflict management systems in organizations is considered to be a significant new development in the USA. The next section evaluates evidence and suggests that a similar pattern of workplace conflict management innovation is not occurring in other Anglo-American countries. After this evaluation, it is suggested that the institutional context in the USA creates uniquely strong incentives for organizations to adopt integrated bundles of ADR practices at the workplace - causing the emergence of conflict management systems to be a case of ‘American exceptionalism’. The following section argues that in the absence of strong institutional incentives to do so, organizations are unlikely to move radically away from established conflict management systems. The penultimate section explains that even in the presence of organizational inertia, conflict management practices seldom stay the same and uses research in the Irish context to suggest that organizations sometimes use an evolutionary approach to upgrade conflict management practices in an incremental yet continuous manner. The final section presents a number of case studies of this evolutionary approach to conflict management innovation. The conclusions bring together the arguments of the paper