Creativity and the ability to reason analogically have a strong relationship [18, 19, 29, 23]. For example, many of the greatest lines in literature make use of familiar analogical processes: “A rose by any other name would smell as sweet” only makes sense if that rose and its name are understood to correspond to Romeo and his family name (analogical mapping). The subsequent analogical inferenc...

We introduce AHEAD (Analogical Hypothesis Elaborator for Activity Detection), a software system we are developing for the DARPA EELD (Evidence Extraction and Link Discovery) program. AHEAD performs case-based hypothesis elaboration using process models. We are applying AHEAD, which embodies a domain-independent approach, to elaborate hypothesized hostile activities. In this application, AHEAD i...

We present an approach to generate novel computer game levels that blend different game concepts in an unsupervised fashion. Our primary contribution is an analogical reasoning process to construct blends between level design models learned from gameplay videos. The models represent probabilistic relationships between elements in the game. An analogical reasoning process maps features between t...

This paper presents an experimental study of the influence that the anxiety state may have on analogical mapping. Contrary to the well-known study of Tohill & Holyoak (2000), where the anxiety state impeded the analogical mapping, in this study participants in the anxiety state were significantly more inclined to produce a relational choice which is structurally consistent with the target, even...

Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i.e., how to move from the unruly, broad set of concepts used in everyday life to a concise, formal vocabulary of abstractions that can be used effectively for problem solving. This paper describes how the Companions cog...

Analogical modeling (AM) is a memory based model. Known algorithms implementing AM depend on investigating all combinations of matching features, which in the worst case is exponential (O(2)). We formulate a representation theorem on analogical modeling which is used for implementing a range of approximations to AM with a much lower complexity. We will demonstrate how our model can be modified ...

We propose to characterize structural similarity between source and target problems by the type and size of their structural overlap. Size of structural overlap is captured by a measure of graph-distance. We investigated the influence of structural overlap on transfer success in analogical problem solving in two experiments. In both experiments, for a fixed source problem one of five target pro...

Sensitivity to the causal structure underlying phenomena is critical to expert understanding. Fostering such understanding in learners is therefore a key goal in education. We hypothesized that observing analogical gestures—which represent relational information in visuospatial format— would lead learners to notice and reason about underlying causal patterns, such as positive and negative feedb...

We are concerned with the practical feasibility of the neural basis of analogical mapping. All existing connectionist models of analogical mapping rely to some degree on localist representation (each concept or relation is represented by a dedicated unit/neuron). These localist solutions are implausible because they need too many units for human-level competence or require the dynamic re-wiring...

In this paper we propose an algebraic method for solving proportional analogy problems involving sequential patterns. In this approach, sequential patterns are considered as elements of an algebra. The gestalt that is assigned to a pattern is represented by the term of the algebra that denotes it. Most patterns are ambiguous: there are diierent terms that correspond to a pattern, representing d...