Abstract—We present a structured model of context that supports an integrated approach to language acquisition and use. The model extends an existing formal notation, Embodied Construction Grammar (ECG), with representations for tracking both entities and events in discourse and situational context. The notation employs an intermediate level of granularity between low-level sensorimotor representations (such as that suitable for dynamic models of action and events for grounded language learning) and the more schematic representations needed for learning and using grammar. The resulting model allows existing systems for simulation-based language understanding and comprehension-driven grammar learning to represent, interpret and acquire a variety of contextually grounded construction. I. INTRODUCTION Language acquisition is inherently context-dependent: every utterance a child hears is rooted within an ongoing stream of activity involving multiple participants interacting in structured ways. From the earliest communicative gestures and first words through word combinations and grammatical constructions, children learn not just the sound patterns (or gestures) of their input language(s) but also the ways in which those patterns are used to achieve communicative goals, all within specific situational contexts. Most theories of language acquisition acknowledge that by the time children acquire their first words, they have amassed considerable sensorimotor and social-interactional expertise, which are deployed to infer, express and achieve goals. Nonetheless, aspects of situational and pragmatic context play a relatively limited role in most models of the acquisition of syntax. In some cases, this omission is theoretically motivated: models based on syntactico-centric theories (including Generative Grammar and its successors) restrict their attention to formal syntax, with detailed semantic and pragmatic information relegated to either the lexicon or general inference processes. From a more practical perspective, situational context poses far greater challenges for both representation and data collection than the simple surface strings assumed as input in more traditional approaches. Two current streams in the literature take a more inclusive approach to linguistic representation. Construction-based theories of grammar [1-3], along with work in the broader cognitive linguistics community, take the basic unit of Both authors are with the Department of Electrical Engineering and Computer Science, University of California, Berkeley, and the International Computer Science Institute, 1947 Center Street Ste. 600, Berkeley, CA 94704. (phone: 510-666-2889; email: {nchang, emok}@ icsi.berkeley.edu). language to be a construction, or form-meaning mapping. In particular, syntactic patterns are, in this framework, inherently paired with aspects of meaning, where meaning encompasses any aspect of semantics or pragmatics, including the context of use. On this view, syntactic patterns and grammatical markers may differ from lexical items in size of level of abstraction, but they can still be represented, used and learned in similar ways. In particular, usage-based theories of construction learning [4, 5] have proposed that children’s earliest constructions are lexically specific and motivated by individual instances of use, only gradually giving rise to the more abstract patterns of form and meaning associated with grammar. The other relevant stream comes from computational models of grounded language learning. These models take a bottom-up approach that emphasizes the situated nature of language learning, exposing robotic and simulated agents to sensorimotor input accompanied by linguistic input in a dynamic environment [6-8]. While work in this area has focused on lexical acquisition and concrete physical domains, the background assumptions provide a more realistic approximation of the child’s ability to exploit situational context in language learning. The current work takes an approach that is consistent with both of these streams in addressing the need for incorporating context into models of grammar learning. We build on previous work on Embodied Construction Grammar (ECG) [9], a computational formalism designed to support models of language acquisition and use. The formalism captures many insights from cognitive linguistics and construction-based theories of language, and provides a suitable target of learning for all stages of language learning. Its meaning representations are also, however, embodied, in that they provide an interface to dynamic structures that model aspects of action and perception. It thus provides an intermediate level of representation between abstract linguistic theory and sensorimotor grounding. In this paper we present a structured, dynamic context representation that addresses the need for context in language understanding. We first review some linguistic phenomena that shed light on the role of context in early child language, drawing examples from typologically diverse languages (Section II) before summarizing the theoretical framework within which our current work is situated (Sections III & IV). We then describe extensions to the ECG framework that allow constructions to refer to structured representations of both situational and discourse context and express diverse contextual constraints (Section A Structured Context Model for Grammar Learning Nancy Chang and Eva MokV). Finally, we show how interleaved processes of constructional analysis, reference resolution and grammar learning can exploit the resulting integrated context model to express, understand and learn a variety of contextually grounded constructions (Section VI). II. THE PROBLEM OF CONTEXT The contextual fluidity of language use has been extensively documented in the literature: speakers use language to accomplish communicative goals rooted in specific contexts, and many utterances make sense only