Establishing the chronology of the Vedas has interested scholars for the last two centuries. The oldest among them is Rig-Veda which has ten Mandalas, each composed separately. In this paper, we look at deciphering plausible pointers to the internal chronology of the Mandalas, by focusing on Gods and Goddesses worshiped in different Mandalas. We apply text analysis to the Mandalas using Clustering Techniques based on Cosine Similarity. Then we represent the association of deities with Mandalas using a grid-based Social Network that is amenable to chronological analysis and demonstrates the benefits of using Social Network Analysis for the problem at hand. Further, we analyze references to rivers to arrive at additional correlations. The approach used can be deployed generically to analyze other kinds of references and mentions and arrive at more substantive inferences.

We present an architecture and system for understanding novel behaviors of an observed agent. The two main features of our approach are the adoption of Dennett's intentional stance and analogical reasoning as one of the main computational mechanisms for understanding unforeseen experiences. Our approach uses analogy with past experiences to construct hypothetical rationales that explain the behavior of an observed agent. Moreover, we view analogies as partial; thus multiple past experiences can be blended to analogically explain an unforeseen event, leading to greater inferential flexibility. We argue that this approach results in more meaningful explanations of observed behavior than approaches based on surface-level comparisons. A key advantage of behavior explanation over classification is the ability to i) take appropriate responses based on reasoning and ii) make non-trivial predictions that allow for the verification of the hypothesized explanation. We provide a simple use case to demonstrate novel experience understanding through analogy in a gas station environment.

However, before ice core data can have scientific value, the chronology must be inferred by estimating the age as a function of depth. Under certain conditions, chemicals locked in the ice display quasi-periodic cycles that delineate annual layers. Manually counting these noisy seasonal patterns to infer the chronology can be an imperfect and time-consuming process, and does not capture uncertainty in a principled fashion. In addition, several ice cores may be collected from a region, introducing an aspect of spatial correlation between them. We present an exploration of the use of probabilistic models for automatic dating of ice cores, using probabilistic programming to showcase its use for prototyping, automatic inference and maintainability, and demonstrate common failure modes of these tools.

To provide a foundation for conceptual modeling, ontologies have been introduced to specify the entities, the existences of which are acknowledged in the model. Ontologies are essential components as mechanisms to model a portion of reality in software engineering. In this context, a model refers to a description of objects and processes that populate a system. Developing such a description constrains and directs the design, development, and use of the corresponding system, thus avoiding such difficulties as conflicts and lack of a common understanding. In this cross-area research between modeling and ontology, there has been a growing interest in the development and use of domain ontologies (e.g., Resource Description Framework, Ontology Web Language). This paper contributes to the establishment of a broad ontological foundation for conceptual modeling in a specific domain through proposing a workable ontology (abbreviated as TM). A TM is a one-category ontology called a thimac (things/machines) that is used to elaborate the design and analysis of ontological presumptions. The focus of the study is on such notions as change, event, and time. Several current ontological difficulties are reviewed and remodeled in the TM. TM modeling is also contrasted with time representation in SysML. The results demonstrate that a TM is a useful tool for addressing these ontological problems.

We present work toward computationally defining a model of narrative comprehension vis-à-vis memory of narrative events, via an automated planning knowledge representation, capable of being used in a narrative generation context.

A growing body of work in games research, both generative and analytic, seeks to characterize the relationship between a player’s understanding of an interactive narrative and her options for action within it. This paper provides several definitions that collectively serve as a basis for a model of the user’s comprehension of an unfolding story in a game. Central to this approach, we define the notion of narrative affordance. In essence, a game provides a narrative affordance for some course of action when a player can imagine that course of action as part of a story that completes their current story experience. To define narrative affordance, we draw links from cognitive models of narrative comprehension and a range of research on affordance, which we couple with planning approaches to story and discourse generation. In our approach, we view the creation of an interactive narrative that provides a high degree of agency as a discourse generation problem. We posit that an interactive narrative system must reason about the content and organization of its communication with a player in order to prompt a player’s understanding about the game’s story and her role in it. This paper ends by pointing toward a research direction intended to provide insight into a range of aspects of interactive narrative, including role, genre, choice and agency.

The formalizations of periods of time inside a linear model of Time are usually based on the notion of intervals, that may contain or may not their endpoints. This is not enought when the periods are written in terms of coarse granularities with respect to the event taken into account. For instance, how to express the inter-war period in terms of a {\em years} interval? This paper presents a new type of intervals, neither open, nor closed or open-closed and the extension of operations on intervals of this new type, in order to reduce the gap between the discourse related to temporal relationship and its translation into a discretized model of Time.

It can be seen that a great deal of worthwhile material has now been generated about computer chess. There is also quite a bit of nonsense by persons who have never built a program. Several groups with excellent programs have done little publishing, although I can hardly blame them since their work requires much time and is usually unsupported by any funding agencies. Certain staples have given rise to duplication: All but one of the books published explain the depth-first alpha-beta procedure. We expect that by far the largest portion of our readers will be scientists interested in updating their knowledge of the subject.