Update introduction of least core notebook as suggested

Author: AnesBenmerzoug

notebooks/least_core_basic.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "This notebook introduces Least Core methods for the computation of data values using pyDVL.\n",
     "\n",
-    "Whereas the Shapley values define a fair way to distribute data values amongst all data points when the entire training set is used. But they do not consider the question of stability: Would some data points get a better payoff by using smaller subsets?\n",
+    "Shapley values define a fair way of distributing the worth of the whole training set when every data point is part of it. But they do not consider the question of stability of subsets: Could some data points obtain a higher payoff if they formed smaller subsets? It is argued that this might be relevant if data providers are paid based on data value, since Shapley values can incentivise them not to contribute their data to the \"grand coalition\", but instead try to form smaller ones. Whether this is of actual practical relevance is debatable, but in any case, the least core is an alternative tool available for any task of Data Valuation\n",
     "\n",
     "The Core is another approach to compute data values originating in cooperative game theory that attempts to answer those questions. It is the set of feasible payoffs that cannot be improved upon by a coalition of the participants.\n",
     "\n",