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In their detailed theoretical discussion of how to define tool use in the animal and human behavioural literature, St. Amant & Horton also revised Beck's now classic definition of tool use to include those instances of tool use which "mediate the flow of information" between the tool user and the environment, including both direct physical interactions with objects, and communicative gestures.
Additionally, given that we only analyzed video footage of the chimpanzees' behavior, on, or within 1 m of, the artificial termite mound, it is possible we did not code all instances of tool modification.
135– 137 Certainly, we have no evidence of action syntax in animals even approaching the complexity of making a pot of coffee: the closest would be certain instances of tool use in some chimpanzee populations.
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To address the potential complexity of the cognitive processes involved in tool use, it is useful to examine instances of tool-oriented behaviour that, at least at first sight, appear to be highly sophisticated [3].
It is the only known instance of tool use by dolphins in the wild.
To exploit parallelism in a workstation with one or more multi-core CPUs, one can either run a single instance of a tool with multithreading on all available CPU cores, or run multiple instances of that tool, each instance using only a fraction of the CPU cores.
Prior to 1.4 million years ago, all reliable instances of stone tool occurrences outside of Africa are represented by cores and flake tools rather than handaxe technology [2], [17], [53].
Even on a single, multi-core machine, the runtime can be reduced significantly as it is often more efficient to run multiple instances of a tool, each instance with a limited number of threads, compared with running only a single instance of that tool with many threads.
Therefore, multiple instances of a tool can be run in parallel on a subset of the data.
On the other hand, the maximum number of parallel instances of a tool than can be run on a machine might be limited due to memory constraints.
To achieve optimal performance on computer clusters with multi-core nodes, Halvade can be configured to run multiple parallel instances of a tool per node, each instance using a limited number of threads.
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