Negmas

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* Minor bugfixes

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* Adding simple tournaments and testing them
* improving plotting and minor typing enhancement
* bugfix in time-based
* Reducing verbosity
* passing kwargs back to Negotitors
* Adding simple tournaments
* Fixing a pandas warning
* Renaming Scenario.agenda -> outcome_space

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* Switching to readthedocs.io
* doc update
* adding RandomAlwaysAcceptingNegotiator
* Upgrading CI tests to use python 3.12 by default
* avoid genius when calculating coverage
* Do not test notebooks before release (avoid genius)
* Empty results when a tournament has no scores

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* Adding RandomOfferGuaranteedAcceptance negotiator
* Fixing some failures in testing some genius agents
* [Snyk] Security upgrade pillow from 9.5.0 to 10.0.1
* [Snyk] Security upgrade werkzeug from 2.2.3 to 3.0.1
* [Snyk] Security upgrade pillow from 9.5.0 to 10.0.0
* fix: docs/requirements.txt to reduce vulnerabilities
* Updating tutorials, adding a tournament there
* Fixing an installation bug: hypothesis was needed to run test_situated under negmas/tests. This prevented users from running the fast set of tests after installation.
* cartesian_tournament to run a simple tournament
- cartesian_tournament runs a simple tournament similar to Genius tournaments.
- create_cartesian_tournament creates a simple Cartesian tournament but does not run it. To run the tournament, call run_tournament passing it the returned path from create_cartesian_tournament.
* fix: requirements-visualizer.txt to reduce vulnerabilities
* Group2 defaults to Y2015Group2 in gnegotaitors
* adding Ateamagent beside AteamAgent
* Correcting few gnegotiator names
* standardizing some gnegotiator names
* renaming ateamAgent -> AteamAgent in genius
* Adding some missing Genius negotiators to gnegotiators.py

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* various bugfixes
* Updating ginfo (Genius Information) with ANAC competition information up to the end of genius support and partial information for geniusweb years

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* removing offer from SAO's respond() method.
* allowing users to step worlds from the point of view of a set of agents ignoring simulation step boundaries and passing external actions if needed. See World.step() for details.