English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Our goal is to enable a robot to learn how to sequence its actions to performtasks specified as natural language instructions, given successfuldemonstrations from a human partner. The ability to plan high-level tasks canbe factored as (i) inferring specific goal predicates that characterize thetask implied by a language instruction for a given world state and (ii)synthesizing a feasible goal-reaching action-sequence with such predicates. Forthe former, we leverage a neural network prediction model, while utilizing asymbolic planner for the latter. We introduce a novel neuro-symbolic model,GoalNet, for contextual and task dependent inference of goal predicates fromhuman demonstrations and linguistic task descriptions. GoalNet combines (i)learning, where dense representations are acquired for language instruction andthe world state that enables generalization to novel settings and (ii)planning, where the cause-effect modeling by the symbolic planner eschewsirrelevant predicates facilitating multi-stage decision making in largedomains. GoalNet demonstrates a significant improvement (51%) in the taskcompletion rate in comparison to a state-of-the-art rule-based approach on abenchmark data set displaying linguistic variations, particularly formulti-stage instructions.

GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction Following